From 35aa323808435e22dc5c10cd611599e45b84c238 Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Mon, 26 Jun 2023 10:47:47 +0200 Subject: [PATCH 01/23] removed duplicate call to organoiDL in run --- napari_organoid_counter/_widget.py | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index d10f596..a75bd21 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -208,16 +208,12 @@ def _on_run_click(self): """ Is called whenever Run Organoid Counter button is clicked """ # check if model has been loaded if self.organoiDL is None: - if os.path.isfile(self.model_path): - self.organoiDL = OrganoiDL(self.viewer.layers[self.image_layer_name].scale, - model_checkpoint=self.model_path - ) - else: + if not os.path.isfile(self.model_path): #show_info('Make sure to select the correct model path!') show_info('Model not found locally. Downloading default model instead!') - self.organoiDL = OrganoiDL(self.viewer.layers[self.image_layer_name].scale, - model_checkpoint=self.model_path - ) + self.organoiDL = OrganoiDL(self.viewer.layers[self.image_layer_name].scale, + model_checkpoint=self.model_path + ) # and if an image has been loaded if not self.image_layer_name: From e94224500f0c1ed7928e3c85d5bdc6e498d1b3ab Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Fri, 30 Jun 2023 17:27:35 +0200 Subject: [PATCH 02/23] added functions to set scale and model in organoidl, fixed adding labels to backend --- napari_organoid_counter/_orgacount.py | 35 ++++++++++++++++++--------- napari_organoid_counter/_widget.py | 30 +++++++++++++---------- 2 files changed, 40 insertions(+), 25 deletions(-) diff --git a/napari_organoid_counter/_orgacount.py b/napari_organoid_counter/_orgacount.py index 3f22a94..12aaf42 100644 --- a/napari_organoid_counter/_orgacount.py +++ b/napari_organoid_counter/_orgacount.py @@ -5,33 +5,36 @@ import subprocess class OrganoiDL(): - def __init__(self, - img_scale, - model_checkpoint=None): + def __init__(self): super().__init__() self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') self.cur_confidence = 0.05 self.cur_min_diam = 30 - self.model = frcnn(num_classes=2, rpn_score_thresh=0, box_score_thresh = self.cur_confidence) - self.model_checkpoint = model_checkpoint - if not os.path.isfile(self.model_checkpoint): - self.download_model() - self.load_model_checkpoint(self.model_checkpoint) - self.model = self.model.to(self.device) self.transfroms = ToTensor() - self.img_scale = img_scale + self.model = None + self.img_scale = [0,0] self.pred_bboxes = {} self.pred_scores = {} self.pred_ids = {} self.next_id = {} + def set_scale(self, img_scale): + self.img_scale = img_scale + + def set_model(self, model_checkpoint): + self.model = frcnn(num_classes=2, rpn_score_thresh=0, box_score_thresh = self.cur_confidence) + if not os.path.isfile(model_checkpoint): + model_checkpoint = self.download_model() + self.load_model_checkpoint(model_checkpoint) + self.model = self.model.to(self.device) + def download_model(self): subprocess.run(["zenodo_get","10.5281/zenodo.7708763","-o", "model"]) - self.model_checkpoint = os.path.join(os.getcwd(), 'model', 'model_v1.ckpt') #zenodo_get(['10.5281/zenodo.7708763']) - + return os.path.join(os.getcwd(), 'model', 'model_v1.ckpt') + def load_model_checkpoint(self, model_path): ckpt = torch.load(model_path, map_location=self.device) self.model.load_state_dict(ckpt) #.state_dict()) @@ -131,7 +134,10 @@ def update_bboxes_scores(self, shapes_name, new_bboxes, new_scores, new_ids): self.pred_bboxes[shapes_name] = new_bboxes self.pred_scores[shapes_name] = new_scores self.pred_ids[shapes_name] = new_ids + self.next_id[shapes_name] = len(new_ids)+1 + elif len(new_ids)==0: return + else: min_diameter_x = self.cur_min_diam / self.img_scale[0] min_diameter_y = self.cur_min_diam / self.img_scale[1] @@ -167,3 +173,8 @@ def update_next_id(self, shapes_name, c=0): self.next_id[shapes_name] = c else: self.next_id[shapes_name] += 1 + def remove_shape_from_dict(self, shapes_name): + del self.pred_bboxes[shapes_name] + del self.pred_scores[shapes_name] + del self.pred_ids[shapes_name] + del self.next_id[shapes_name] diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index a75bd21..f7474fd 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -79,7 +79,7 @@ def __init__(self, self.save_layer_name = '' self.cur_shapes_name = '' self.cur_shapes_layer = None - self.organoiDL = None + self.organoiDL = OrganoiDL() self.num_organoids = 0 self.original_images = {} self.original_contrast = {} @@ -206,15 +206,14 @@ def _on_preprocess_click(self): def _on_run_click(self): """ Is called whenever Run Organoid Counter button is clicked """ - # check if model has been loaded - if self.organoiDL is None: + # check if model has been loaded and scale set + if self.organoiDL.model is None: if not os.path.isfile(self.model_path): #show_info('Make sure to select the correct model path!') show_info('Model not found locally. Downloading default model instead!') - self.organoiDL = OrganoiDL(self.viewer.layers[self.image_layer_name].scale, - model_checkpoint=self.model_path - ) - + self.organoiDL.set_model(model_checkpoint=self.model_path) + if self.organoiDL.img_scale[0]==0: self.organoiDL.set_scale(self.viewer.layers[self.image_layer_name].scale) + # and if an image has been loaded if not self.image_layer_name: show_info('Please load an image first and try again!') @@ -257,6 +256,8 @@ def _on_choose_model_clicked(self): if fd.exec_(): self.model_path = fd.selectedFiles()[0] self.model_textbox.setText(self.model_path) + ''' + ############# REMOVE?????????????? # initialise organoiDL instance with the model path chosen try: if self.cur_shapes_layer is not None: @@ -270,6 +271,7 @@ def _on_choose_model_clicked(self): model_checkpoint=self.model_path, ) except: show_info('Could not load model - make sure you are loading the correct file (with .ckpt ending)') + ''' def _on_window_sizes_changed(self): """ Is called whenever user changes the window sizes text box """ @@ -286,11 +288,9 @@ def _on_downsampling_changed(self): def _rerun(self): """ Is called whenever user changes one of the two parameter sliders """ # check if OrganoiDL instance exists - create it if not and set there current boxes, scores and ids - if self.organoiDL is None: - self.organoiDL = OrganoiDL(self.cur_shapes_layer.scale, - model_checkpoint=self.model_path) - self.organoiDL.update_next_id(self.cur_shapes_name, len(self.cur_shapes_layer.scale)+1) - + if self.organoiDL.img_scale[0]==0: self.organoiDL.set_scale(self.cur_shapes_layer.scale) + self.organoiDL.update_next_id(self.cur_shapes_name, len(self.cur_shapes_layer.scale)+1) + # make sure to add info to cur_shapes_layer.metadata to differentiate this action from when user adds/removes boxes with set_dict_key( self.cur_shapes_layer.metadata, 'napari-organoid-counter:_rerun', True): # first update bboxes in organoiDLin case user has added/removed @@ -427,6 +427,10 @@ def _update_added_shapes(self, added_items): # get the bounding box and update the displayed number of organoids self._update_num_organoids(len(self.cur_shapes_layer.data)) # listen for a data change in the current shapes layer + self.organoiDL.update_bboxes_scores(self.cur_shapes_name, + self.cur_shapes_layer.data, + self.cur_shapes_layer.properties['scores'], + self.cur_shapes_layer.properties['box_id']) self.cur_shapes_layer.events.data.connect(self.shapes_event_handler) def _update_remove_shapes(self, removed_layers): @@ -439,7 +443,7 @@ def _update_remove_shapes(self, removed_layers): self.output_layer_selection.removeItem(item_id) if removed_layer==self.cur_shapes_name: self._update_num_organoids(0) - self.organoiDL = None + self.organoiDL.remove_shape_from_dict(self.cur_shapes_name) self.cur_shapes_name = '' # DO SOMETHING! def shapes_event_handler(self, event): From 18e93b9f4894f9af64b61875c996c07d887fa39b Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Tue, 4 Jul 2023 17:14:18 +0200 Subject: [PATCH 03/23] added documentation to orgacount class --- napari_organoid_counter/_orgacount.py | 39 +++++++++++++++++++++++---- napari_organoid_counter/_widget.py | 1 - 2 files changed, 34 insertions(+), 6 deletions(-) diff --git a/napari_organoid_counter/_orgacount.py b/napari_organoid_counter/_orgacount.py index 12aaf42..9700c13 100644 --- a/napari_organoid_counter/_orgacount.py +++ b/napari_organoid_counter/_orgacount.py @@ -5,6 +5,36 @@ import subprocess class OrganoiDL(): + ''' + The back-end of the organoid counter widget + Attributes + ---------- + device: torch.device + The current device, either 'cpu' or 'gpu:0' + cur_confidence: float + The confidence threshold of the model + cur_min_diam: float + The minimum diameter of the organoids + transfroms: torchvision.transforms.ToTensor + The transformation for converting numpy image to tensor so it can be given as an input to the model + model: frcnn + The Faster R-CNN model + img_scale: list of floats + A list holiding the image resolution in x and y + pred_bboxes: dict + Each key will be a set of predictions of the model, either past or current, and values will be the numpy arrays + holding the predicted bounding boxes + pred_scores: dict + Each key will be a set of predictions of the model abd the values will hold the confidence of the model for each + predicted bounding box + pred_ids: dict + Each key will be a set of predictions of the model abd the values will hold the box id for each + predicted bounding box + next_id: dict + Each key will be a set of predictions of the model abd the values will hold the next id to be attributed to a + newly added box + + ''' def __init__(self): super().__init__() @@ -14,7 +44,7 @@ def __init__(self): self.transfroms = ToTensor() self.model = None - self.img_scale = [0,0] + self.img_scale = [0., 0.] self.pred_bboxes = {} self.pred_scores = {} self.pred_ids = {} @@ -31,17 +61,16 @@ def set_model(self, model_checkpoint): self.model = self.model.to(self.device) def download_model(self): - subprocess.run(["zenodo_get","10.5281/zenodo.7708763","-o", "model"]) - #zenodo_get(['10.5281/zenodo.7708763']) + ''' Downloads the model from zenodo and returns the path where it is stored ''' + subprocess.run(["zenodo_get", "10.5281/zenodo.7708763", "-o", "model"]) return os.path.join(os.getcwd(), 'model', 'model_v1.ckpt') def load_model_checkpoint(self, model_path): + ''' Loads the model checkpoint ''' ckpt = torch.load(model_path, map_location=self.device) self.model.load_state_dict(ckpt) #.state_dict()) def sliding_window(self, test_img, step, window_size, rescale_factor, prepadded_height, prepadded_width, pred_bboxes=[], scores_list=[]): - - #img_height, img_width = test_img.size(2), test_img.size(3) for i in range(0, prepadded_height, step): for j in range(0, prepadded_width, step): diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index f7474fd..ce4c7b8 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -444,7 +444,6 @@ def _update_remove_shapes(self, removed_layers): if removed_layer==self.cur_shapes_name: self._update_num_organoids(0) self.organoiDL.remove_shape_from_dict(self.cur_shapes_name) - self.cur_shapes_name = '' # DO SOMETHING! def shapes_event_handler(self, event): """ From 88c239bfb11134b2eee0e0fcab20f2606f3b7cba Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Wed, 5 Jul 2023 17:10:14 +0200 Subject: [PATCH 04/23] added info boxes on params at hover time --- napari_organoid_counter/_widget.py | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index ce4c7b8..86df28f 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -576,15 +576,21 @@ def _setup_window_sizes_box(self): """ #self.window_sizes_box = QGroupBox() hbox = QHBoxLayout() + info_text = ("Typically a ratio of 512 to 1 between window size and downsampling rate will give good results, (larger window \n" + "sizes can lead to a drop in performance). Note that small window sizes will signicantly impact the runtime of the \n" + "algorithm. For organoids of different sizes consider setting multiple windows sizes. Hit Enter for the change to \n" + "take effect.") # setup label window_sizes_label = QLabel('Window sizes: [size1, size2, ...]', self) window_sizes_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) + window_sizes_label.setToolTip(info_text) # setup textbox self.window_sizes_textbox = QLineEdit(self) text = [str(window_size) for window_size in self.window_sizes] text = ','.join(text) self.window_sizes_textbox.setText(text) self.window_sizes_textbox.returnPressed.connect(self._on_window_sizes_changed) + self.window_sizes_textbox.setToolTip(info_text) # and add all these to the layout hbox.addWidget(window_sizes_label) hbox.addWidget(self.window_sizes_textbox) @@ -599,15 +605,22 @@ def _setup_downsampling_box(self): """ #self.downsampling_box = QGroupBox() hbox = QHBoxLayout() + info_text = ("To detect large organoids (and ignore smaller structures) you can increase the downsampling rate. \n" + "If your organoids are small and are being missed by the algorithm, consider reducing the downsampling\n" + "rate. The number of downsampling inputs should match the number of windows sizes. Hit Enter for the \n" + "change to take effect. See window sizes for more info.") + # setup label downsampling_label = QLabel('Downsampling: [ds1, ds2, ...]', self) downsampling_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) + downsampling_label.setToolTip(info_text) # setup textbox self.downsampling_textbox = QLineEdit(self) text = [str(ds) for ds in self.downsampling] text = ','.join(text) self.downsampling_textbox.setText(text) self.downsampling_textbox.returnPressed.connect(self._on_downsampling_changed) + self.downsampling_textbox.setToolTip(info_text) # and add all these to the layout hbox.addWidget(downsampling_label) hbox.addWidget(self.downsampling_textbox) From 2455d0cf2520d71220b4b78d37a86f706fbc73f9 Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Wed, 5 Jul 2023 17:39:31 +0200 Subject: [PATCH 05/23] added progress bars during sliding window --- napari_organoid_counter/_orgacount.py | 11 +++++++---- napari_organoid_counter/_widget.py | 6 +++++- 2 files changed, 12 insertions(+), 5 deletions(-) diff --git a/napari_organoid_counter/_orgacount.py b/napari_organoid_counter/_orgacount.py index 9700c13..3e6d735 100644 --- a/napari_organoid_counter/_orgacount.py +++ b/napari_organoid_counter/_orgacount.py @@ -1,8 +1,10 @@ import os import torch from torchvision.transforms import ToTensor -from napari_organoid_counter._utils import frcnn, prepare_img, apply_nms, convert_boxes_to_napari_view, convert_boxes_from_napari_view, get_diams +from napari.utils import progress import subprocess +from napari_organoid_counter._utils import frcnn, prepare_img, apply_nms, convert_boxes_to_napari_view, convert_boxes_from_napari_view, get_diams + class OrganoiDL(): ''' @@ -71,9 +73,10 @@ def load_model_checkpoint(self, model_path): self.model.load_state_dict(ckpt) #.state_dict()) def sliding_window(self, test_img, step, window_size, rescale_factor, prepadded_height, prepadded_width, pred_bboxes=[], scores_list=[]): - - for i in range(0, prepadded_height, step): - for j in range(0, prepadded_width, step): + #with progress(range(steps)) as pbr: + for i in progress(range(0, prepadded_height, step)): + #for i in range(0, prepadded_height, step): + for j in progress(range(0, prepadded_width, step)): # crop img_crop = test_img[:, :, i:(i+window_size), j:(j+window_size)] diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index 86df28f..a32e785 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -233,6 +233,8 @@ def _on_run_click(self): if labels_layer_name in self.shape_layer_names: show_info('Found existing labels layer. Please remove or rename it and try again!') return + # show activity docker for progrgess bar while running + self.viewer.window._status_bar._toggle_activity_dock(True) # run inference self.organoiDL.run(img_data, labels_layer_name, @@ -241,7 +243,9 @@ def _on_run_click(self): window_overlap = 0.5) # set the confidence threshold, remove small organoids and get bboxes in format o visualise bboxes, scores, box_ids = self.organoiDL.apply_params(labels_layer_name, self.confidence, self.min_diameter) - + # hide activcity dock on completion + self.viewer.window._status_bar._toggle_activity_dock(False) + # update widget with results self._update_vis_bboxes(bboxes, scores, box_ids, labels_layer_name) # and update cur_shapes_name to newly created shapes layer self.cur_shapes_name = labels_layer_name From f601a3689647c60cc122de5f2c880098734cf452 Mon Sep 17 00:00:00 2001 From: Christina Bukas <31160776+christinab12@users.noreply.github.com> Date: Fri, 7 Jul 2023 09:09:26 +0200 Subject: [PATCH 06/23] Update README.md --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 39211b2..e82bf7e 100644 --- a/README.md +++ b/README.md @@ -41,6 +41,8 @@ Then run napari on your terminal. Checkout our *What's New in v2* [here](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/.napari/DESCRIPTION.md#whats-new-in-v2). ## How to use? +After installing, you can type ```napari``` in your terminal and select the plugin from the drop down menu. + For more information on this plugin, its' intended audience, as well as Quickstart guide go to our [Quickstart guide](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/.napari/DESCRIPTION.md#quickstart). ## Contributing From a345b83e1bcb9489304fb4946df97a57857d95d0 Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Fri, 7 Jul 2023 12:18:50 +0200 Subject: [PATCH 07/23] removed if check for organoidl instance in model loading --- napari_organoid_counter/_widget.py | 24 +++++++++++++++--------- 1 file changed, 15 insertions(+), 9 deletions(-) diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index a32e785..67ea994 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -206,41 +206,47 @@ def _on_preprocess_click(self): def _on_run_click(self): """ Is called whenever Run Organoid Counter button is clicked """ - # check if model has been loaded and scale set - if self.organoiDL.model is None: - if not os.path.isfile(self.model_path): - #show_info('Make sure to select the correct model path!') - show_info('Model not found locally. Downloading default model instead!') - self.organoiDL.set_model(model_checkpoint=self.model_path) - if self.organoiDL.img_scale[0]==0: self.organoiDL.set_scale(self.viewer.layers[self.image_layer_name].scale) - - # and if an image has been loaded + + # check if an image has been loaded if not self.image_layer_name: show_info('Please load an image first and try again!') return + # check if model has been loaded and scale set + if not os.path.isfile(self.model_path): + show_info('Model not found locally. Downloading default model instead!') + + self.organoiDL.set_model(model_checkpoint=self.model_path) + if self.organoiDL.img_scale[0]==0: self.organoiDL.set_scale(self.viewer.layers[self.image_layer_name].scale) + # make sure the number of windows and downsamplings are the same if len(self.window_sizes) != len(self.downsampling): show_info('Keep number of window sizes and downsampling the same and try again!') return + # get the current image img_data = self.viewer.layers[self.image_layer_name].data + # check that image is grayscale if len(squeeze_img(img_data).shape) > 2: show_info('Only grayscale images currently supported. Try a different image or process it first and try again!') return + # update the viewer with the new bboxes labels_layer_name = 'Labels-'+self.image_layer_name if labels_layer_name in self.shape_layer_names: show_info('Found existing labels layer. Please remove or rename it and try again!') return + # show activity docker for progrgess bar while running self.viewer.window._status_bar._toggle_activity_dock(True) + # run inference self.organoiDL.run(img_data, labels_layer_name, self.window_sizes, self.downsampling, window_overlap = 0.5) + # set the confidence threshold, remove small organoids and get bboxes in format o visualise bboxes, scores, box_ids = self.organoiDL.apply_params(labels_layer_name, self.confidence, self.min_diameter) # hide activcity dock on completion From 041ef830ec75c857016bf79d36da8bb6a44312b1 Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Mon, 10 Jul 2023 12:05:14 +0200 Subject: [PATCH 08/23] added textboxes next to sliders --- napari_organoid_counter/_widget.py | 99 +++++++++++++++--------------- 1 file changed, 51 insertions(+), 48 deletions(-) diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index 67ea994..d718fbd 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -73,9 +73,9 @@ def __init__(self, self.min_diameter = min_diameter self.confidence = confidence - self.image_layer_names = None + self.image_layer_names = [] self.image_layer_name = None - self.shape_layer_names = None + self.shape_layer_names = [] self.save_layer_name = '' self.cur_shapes_name = '' self.cur_shapes_layer = None @@ -101,7 +101,8 @@ def __init__(self, self.viewer.layers.events.removed.connect(self._removed_layer) self.viewer.layers.selection.events.changed.connect(self._sel_layer_changed) - #self.slider_changed = False # used for changing slider and text of min diameter + self.diameter_slider_changed = False # used for changing slider and text of min diameter + self.confidence_slider_changed = False # used for changing slider and text of confidence threshold def _sel_layer_changed(self, event): cur_layer_list = list(self.viewer.layers.selection) @@ -116,14 +117,10 @@ def _sel_layer_changed(self, event): self.cur_shapes_name = cur_seg_selected.name # update min diameter text and slider with previous value of that layer self.min_diameter = self.stored_diameters[self.cur_shapes_name] - self.min_diameter_slider.setValue(self.min_diameter) - #self.min_diameter_label.setText('Minimum Diameter [um]: ') - self.min_diameter_label.setText('Minimum Diameter [um]: '+str(self.min_diameter)) + self.min_diameter_textbox.setText(str(self.min_diameter)) # update confidence text and slider with previous value of that layer self.confidence = self.stored_confidences[self.cur_shapes_name] - vis_confidence = int(self.confidence*100) - self.confidence_slider.setValue(vis_confidence) - self.confidence_label.setText('Model confidence: '+str(self.confidence)) + self.confidence_textbox.setText(str(self.confidence)) def _added_layer(self, event): # get names of added layers, image and shapes @@ -311,37 +308,50 @@ def _rerun(self): # and get new boxes, scores and box ids based on new confidence and min_diameter values bboxes, scores, box_ids = self.organoiDL.apply_params(self.cur_shapes_name, self.confidence, self.min_diameter) self._update_vis_bboxes(bboxes, scores, box_ids, self.cur_shapes_name) - - def _on_diameter_changed(self): - """ Is called whenever user changes the Minimum Diameter slider """ - self.min_diameter = self.min_diameter_slider.value() - self.min_diameter_label.setText('Minimum Diameter [um]: '+str(self.min_diameter)) - self._rerun() - ''' def _on_diameter_slider_changed(self): """ Is called whenever user changes the Minimum Diameter slider """ + # get current value self.min_diameter = self.min_diameter_slider.value() - self.slider_changed = True + self.diameter_slider_changed = True if int(self.min_diameter_textbox.text())!= self.min_diameter: self.min_diameter_textbox.setText(str(self.min_diameter)) - self._rerun() - self.slider_changed = False + self.diameter_slider_changed = False + # check if no labels loaded yet + if len(self.shape_layer_names)==0: return + self._rerun() def _on_diameter_textbox_changed(self): - if self.slider_changed: return + """ Is called whenever user changes the minimum diameter from the textbox """ + # check if no labels loaded yet + if self.diameter_slider_changed: return self.min_diameter = int(self.min_diameter_textbox.text()) if self.min_diameter_slider.value() != self.min_diameter: self.min_diameter_slider.setValue(self.min_diameter) + if len(self.shape_layer_names)==0: return self._rerun() - ''' - def _on_confidence_changed(self): + def _on_confidence_slider_changed(self): """ Is called whenever user changes the confidence slider """ self.confidence = self.confidence_slider.value()/100 - self.confidence_label.setText('Model confidence: '+str(self.confidence)) + self.confidence_slider_changed = True + if float(self.confidence_textbox.text()) != self.confidence: + self.confidence_textbox.setText(str(self.confidence)) + self.confidence_slider_changed = False + # check if no labels loaded yet + if len(self.shape_layer_names)==0: return self._rerun() - + + def _on_confidence_textbox_changed(self): + """ Is called whenever user changes the confidence value from the textbox """ + if self.confidence_slider_changed: return + self.confidence = float(self.confidence_textbox.text()) + slider_conf_value = int(self.confidence*100) + if self.confidence_slider.value() != slider_conf_value: + self.confidence_slider.setValue(slider_conf_value) + if len(self.shape_layer_names)==0: return + self._rerun() + def _on_image_selection_changed(self): """ Is called whenever a new image has been selected from the drop down box """ self.image_layer_name = self.image_layer_selection.currentText() @@ -655,7 +665,6 @@ def _setup_min_diameter_box(self): """ Sets up the GUI part where the minimum diameter parameter is displayed """ - #self.min_diameter_box = QGroupBox() hbox = QHBoxLayout() # set up the min diameter slider self.min_diameter_slider = QSlider(Qt.Horizontal) @@ -663,32 +672,24 @@ def _setup_min_diameter_box(self): self.min_diameter_slider.setMaximum(100) self.min_diameter_slider.setSingleStep(10) self.min_diameter_slider.setValue(self.min_diameter) - #self.min_diameter_slider.valueChanged.connect(self._on_diameter_slider_changed) - self.min_diameter_slider.valueChanged.connect(self._on_diameter_changed) + self.min_diameter_slider.valueChanged.connect(self._on_diameter_slider_changed) # set up the label - #self.min_diameter_label = QLabel('Minimum Diameter [um]: ', self) - self.min_diameter_label = QLabel('Minimum Diameter [um]: '+str(self.min_diameter), self) - self.min_diameter_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) - ''' + min_diameter_label = QLabel('Minimum Diameter [um]: ', self) + min_diameter_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) # set up text box self.min_diameter_textbox = QLineEdit(self) self.min_diameter_textbox.setText(str(self.min_diameter)) - self.min_diameter_textbox.returnPressed.connect(self._on_diameter_textbox_changed) - ''' + self.min_diameter_textbox.returnPressed.connect(self._on_diameter_textbox_changed) # and add all these to the layout - hbox.addWidget(self.min_diameter_label) - #hbox.addWidget(self.min_diameter_textbox) - hbox.addSpacing(15) - hbox.addWidget(self.min_diameter_slider) - #self.min_diameter_box.setLayout(hbox) - #self.min_diameter_box.setStyleSheet("border: 0px") + hbox.addWidget(min_diameter_label, 4) + hbox.addWidget(self.min_diameter_textbox, 1) + hbox.addWidget(self.min_diameter_slider, 5) return hbox def _setup_confidence_box(self): """ Sets up the GUI part where the confidence parameter is displayed """ - #self.confidence_box = QGroupBox() hbox = QHBoxLayout() # set up confidence slider self.confidence_slider = QSlider(Qt.Horizontal) @@ -697,16 +698,18 @@ def _setup_confidence_box(self): self.confidence_slider.setSingleStep(5) vis_confidence = int(self.confidence*100) self.confidence_slider.setValue(vis_confidence) - self.confidence_slider.valueChanged.connect(self._on_confidence_changed) + self.confidence_slider.valueChanged.connect(self._on_confidence_slider_changed) # set up label - self.confidence_label = QLabel('Model confidence: '+str(self.confidence), self) - self.confidence_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) + confidence_label = QLabel('Model confidence: ', self) + confidence_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) + # set up text box + self.confidence_textbox = QLineEdit(self) + self.confidence_textbox.setText(str(self.confidence)) + self.confidence_textbox.returnPressed.connect(self._on_confidence_textbox_changed) # and add all these to the layout - hbox.addWidget(self.confidence_label) - hbox.addSpacing(15) - hbox.addWidget(self.confidence_slider) - #self.confidence_box.setLayout(hbox) - #self.confidence_box.setStyleSheet("border: 0px") + hbox.addWidget(confidence_label, 3) + hbox.addWidget(self.confidence_textbox, 1) + hbox.addWidget(self.confidence_slider, 6) return hbox ''' From a15478607c81785d7f71afc87fe9d7edc56a2ece Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Mon, 10 Jul 2023 18:05:46 +0200 Subject: [PATCH 09/23] changed default model selection and adding custom model, starting adding new window for download check --- napari_organoid_counter/_orgacount.py | 29 +++++--- napari_organoid_counter/_utils.py | 26 +++++++ napari_organoid_counter/_widget.py | 102 +++++++++++++++----------- napari_organoid_counter/settings.py | 15 ++++ 4 files changed, 119 insertions(+), 53 deletions(-) create mode 100644 napari_organoid_counter/settings.py diff --git a/napari_organoid_counter/_orgacount.py b/napari_organoid_counter/_orgacount.py index 3e6d735..b6a555d 100644 --- a/napari_organoid_counter/_orgacount.py +++ b/napari_organoid_counter/_orgacount.py @@ -3,7 +3,9 @@ from torchvision.transforms import ToTensor from napari.utils import progress import subprocess -from napari_organoid_counter._utils import frcnn, prepare_img, apply_nms, convert_boxes_to_napari_view, convert_boxes_from_napari_view, get_diams + +from napari_organoid_counter._utils import frcnn, prepare_img, apply_nms, convert_boxes_to_napari_view, convert_boxes_from_napari_view, get_diams, return_is_file +from napari_organoid_counter import settings class OrganoiDL(): @@ -45,6 +47,9 @@ def __init__(self): self.cur_min_diam = 30 self.transfroms = ToTensor() + # create cache dir for models if it doesn't exist + settings.MODELS_DIR.mkdir(parents=True, exist_ok=True) + self.model = None self.img_scale = [0., 0.] self.pred_bboxes = {} @@ -55,27 +60,27 @@ def __init__(self): def set_scale(self, img_scale): self.img_scale = img_scale - def set_model(self, model_checkpoint): + def set_model(self, model_name): + # initialise model instance self.model = frcnn(num_classes=2, rpn_score_thresh=0, box_score_thresh = self.cur_confidence) - if not os.path.isfile(model_checkpoint): - model_checkpoint = self.download_model() - self.load_model_checkpoint(model_checkpoint) + # download model if not there already + if not return_is_file(settings.MODELS_DIR, settings.MODELS[model_name]["filename"]): self.download_model() + self.load_model_checkpoint(model_name) self.model = self.model.to(self.device) - def download_model(self): + def download_model(self, model='default'): ''' Downloads the model from zenodo and returns the path where it is stored ''' - subprocess.run(["zenodo_get", "10.5281/zenodo.7708763", "-o", "model"]) - return os.path.join(os.getcwd(), 'model', 'model_v1.ckpt') + subprocess.run(["zenodo_get", settings.MODELS[model]["source"], "-o", settings.MODELS_DIR]) - def load_model_checkpoint(self, model_path): + def load_model_checkpoint(self, model_name): ''' Loads the model checkpoint ''' - ckpt = torch.load(model_path, map_location=self.device) + model_checkpoint = os.path.join(settings.MODELS_DIR, settings.MODELS[model_name]["filename"]) + ckpt = torch.load(model_checkpoint, map_location=self.device) self.model.load_state_dict(ckpt) #.state_dict()) def sliding_window(self, test_img, step, window_size, rescale_factor, prepadded_height, prepadded_width, pred_bboxes=[], scores_list=[]): - #with progress(range(steps)) as pbr: + for i in progress(range(0, prepadded_height, step)): - #for i in range(0, prepadded_height, step): for j in progress(range(0, prepadded_width, step)): # crop diff --git a/napari_organoid_counter/_utils.py b/napari_organoid_counter/_utils.py index 8b10a08..cbbd0e2 100644 --- a/napari_organoid_counter/_utils.py +++ b/napari_organoid_counter/_utils.py @@ -1,4 +1,7 @@ from contextlib import contextmanager +import os +from pathlib import Path + import numpy as np import math import json @@ -12,6 +15,29 @@ from torchvision.models.detection.faster_rcnn import FastRCNNPredictor from torchvision.ops import nms +from napari_organoid_counter import settings + + +def check_for_local_models(): + if not os.path.exists(settings.MODELS_DIR): return + model_names_in_dir = [file for file in os.listdir(settings.MODELS_DIR)] + model_names_in_dict = [settings.MODELS[key]["filename"] for key in settings.MODELS.keys()] + for model_name in model_names_in_dir: + if model_name not in model_names_in_dict and model_name.endswith(settings.MODEL_TYPE): + _ = add_to_dict(model_name) + +def add_to_dict(filepath): + filepath = Path(filepath) + name = filepath.name + stem_name = filepath.stem + settings.MODELS[stem_name] = {"filename": name, "source": "local"} + return stem_name + +def return_is_file(path, filename): + """ Return True if the file exists in path and False otherwise """ + full_path = os.path.join(path, filename) + return os.path.isfile(full_path) + @contextmanager def set_dict_key(dictionary, key, value): """ Used to set a new value in the napari layer metadata """ diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index d718fbd..48c268f 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -8,14 +8,41 @@ from napari.utils.notifications import show_info from PyQt5.QtCore import Qt -from PyQt5.QtWidgets import (QComboBox, QPushButton, QVBoxLayout, QHBoxLayout, QWidget, QSlider, QLabel, QFileDialog, QLineEdit, QGroupBox) +from PyQt5.QtWidgets import (QComboBox, QPushButton, QVBoxLayout, QHBoxLayout, QWidget, QSlider, QLabel, QFileDialog, QLineEdit, QGroupBox, QDialog, QGridLayout) from napari_organoid_counter._orgacount import OrganoiDL -from napari_organoid_counter._utils import apply_normalization, write_to_csv, get_bbox_diameters, write_to_json, get_bboxes_as_dict, squeeze_img, set_dict_key +from napari_organoid_counter._utils import check_for_local_models, add_to_dict, return_is_file, apply_normalization, write_to_csv, get_bbox_diameters, write_to_json, get_bboxes_as_dict, squeeze_img, set_dict_key +from napari_organoid_counter import settings import warnings warnings.filterwarnings("ignore") +class MyInputDialog(QDialog): + def __init__(self, parent: QWidget): + super().__init__(parent) + self.setWindowTitle("Confirm Download") + self.ok_btn = QPushButton("OK") + self.cancel_btn = QPushButton("Cancel") + text = ["Model not found locally. Downloading default model to "+settings.MODELS_DIR+"\n" + "This will only happen once. Click ok to continue or cancel if you do not agree. "] + + layout = QGridLayout() + layout.addWidget(QLabel(text), 0, 0) + layout.addWidget(self.ok_btn, 1, 0) + layout.addWidget(self.cancel_btn, 1, 1) + self.setLayout(layout) + + self.ok_btn.clicked.connect(self.accept) + self.cancel_btn.clicked.connect(self.reject) + + def accept(self) -> None: + self.close() + return + def reject(self) -> None: + self.close() + return + + class OrganoidCounterWidget(QWidget): ''' The widget of the organoid counter @@ -23,8 +50,6 @@ class OrganoidCounterWidget(QWidget): ---------- napari_viewer: string The current napari viewer - model_path: string, default 'model-weights/model_v1.ckpt' - The relative path to the detection model used for organoid counting - will append current working dir to this path window_sizes: list of ints, default [1024] A list with the sizes of the windows on which the model will be run. If more than one window_size is given then the model will run on several window sizes and then combne the results @@ -36,6 +61,8 @@ class OrganoidCounterWidget(QWidget): The model confidence threhsold - equivalent to box_score_thresh of faster_rcnn Attributes ---------- + model_name: str + The name of the default model image_layer_names: list of strings Will hold the names of all the currently open images in the viewer image_layer_name: string @@ -58,7 +85,6 @@ class OrganoidCounterWidget(QWidget): ''' def __init__(self, napari_viewer, - model_path: str = 'model/model_v1.ckpt', window_sizes: List = [1024], downsampling: List = [2], min_diameter: int = 30, @@ -67,7 +93,9 @@ def __init__(self, # assign class variables self.viewer = napari_viewer - self.model_path = os.path.join(os.getcwd(), model_path) + settings.init() + check_for_local_models() + self.model_name = list(settings.MODELS.keys())[0] self.window_sizes = window_sizes self.downsampling = downsampling self.min_diameter = min_diameter @@ -209,10 +237,11 @@ def _on_run_click(self): show_info('Please load an image first and try again!') return # check if model has been loaded and scale set - if not os.path.isfile(self.model_path): - show_info('Model not found locally. Downloading default model instead!') + if not return_is_file(settings.MODELS_DIR, settings.MODELS[self.model_name]["filename"]): + ww = MyInputDialog(self) + ww.exec_() - self.organoiDL.set_model(model_checkpoint=self.model_path) + self.organoiDL.set_model(model_name=self.model_name) if self.organoiDL.img_scale[0]==0: self.organoiDL.set_scale(self.viewer.layers[self.image_layer_name].scale) # make sure the number of windows and downsamplings are the same @@ -255,30 +284,21 @@ def _on_run_click(self): # preprocess the image if not done so already to improve visualisation self._preprocess() + def _on_model_selection_changed(self): + self.model_name = self.model_selection.currentText() + def _on_choose_model_clicked(self): """ Is called whenever browse button is clicked for model selection """ # called when the user hits the 'browse' button to select a model fd = QFileDialog() fd.setFileMode(QFileDialog.AnyFile) if fd.exec_(): - self.model_path = fd.selectedFiles()[0] - self.model_textbox.setText(self.model_path) - ''' - ############# REMOVE?????????????? - # initialise organoiDL instance with the model path chosen - try: - if self.cur_shapes_layer is not None: - scale = self.cur_shapes_layer.scale - elif self.viewer.layers[self.image_layer_name] is not None: - scale = self.viewer.layers[self.image_layer_name].scale - else: - show_info('Could not find a loaded image or annotation file - please load and then select the model') - return - self.organoiDL = OrganoiDL(scale, - model_checkpoint=self.model_path, - ) - except: show_info('Could not load model - make sure you are loading the correct file (with .ckpt ending)') - ''' + model_path = fd.selectedFiles()[0] + import shutil + shutil.copy2(model_path, settings.MODELS_DIR) + model_name = add_to_dict(model_path) + self.model_selection.addItem(model_name) + def _on_window_sizes_changed(self): """ Is called whenever user changes the window sizes text box """ @@ -558,10 +578,9 @@ def _setup_input_box(self): preprocess_btn = QPushButton("Preprocess") preprocess_btn.clicked.connect(self._on_preprocess_click) # and add all these to the layout - hbox.addWidget(image_label) - hbox.addSpacing(5) - hbox.addWidget(self.image_layer_selection) - hbox.addWidget(preprocess_btn) + hbox.addWidget(image_label, 2) + hbox.addWidget(self.image_layer_selection, 4) + hbox.addWidget(preprocess_btn, 4) #self.input_box.setLayout(hbox) #self.input_box.setStyleSheet("border: 0px") return hbox @@ -570,24 +589,25 @@ def _setup_model_box(self): """ Sets up the GUI part where the model path is set """ - #self.model_box = QGroupBox() hbox = QHBoxLayout() # setup the label model_label = QLabel('Model: ', self) model_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) - # setup the model text box - self.model_textbox = QLineEdit(self) - self.model_textbox.setText(self.model_path) + # set up the browse files button - fileOpenButton = QPushButton('Choose',self) + fileOpenButton = QPushButton('Add custom model', self) fileOpenButton.show() fileOpenButton.clicked.connect(self._on_choose_model_clicked) + + # setup drop down option for selecting which image to process + self.model_selection = QComboBox() + for name in settings.MODELS.keys(): self.model_selection.addItem(name) + self.model_selection.currentIndexChanged.connect(self._on_model_selection_changed) + # and add all these to the layout - hbox.addWidget(model_label) - hbox.addWidget(self.model_textbox) - hbox.addWidget(fileOpenButton) - #self.model_box.setLayout(hbox) - #self.model_box.setStyleSheet("border: 0px") + hbox.addWidget(model_label, 2) + hbox.addWidget(self.model_selection, 4) + hbox.addWidget(fileOpenButton, 4) return hbox def _setup_window_sizes_box(self): diff --git a/napari_organoid_counter/settings.py b/napari_organoid_counter/settings.py new file mode 100644 index 0000000..f6b1fbc --- /dev/null +++ b/napari_organoid_counter/settings.py @@ -0,0 +1,15 @@ +from pathlib import Path + +def init(): + + global MODELS + MODELS = { + "default": {"filename": "model_v1.ckpt", "source": "10.5281/zenodo.7708763"} + } + + global MODELS_DIR + MODELS_DIR = Path.home() / ".cache/napari-organoid-counter/models" + + global MODEL_TYPE + MODEL_TYPE = '.ckpt' + From 1dd130e63c3de06b4dc26d49d71c4f8c465af20c Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Wed, 12 Jul 2023 10:49:10 +0200 Subject: [PATCH 10/23] added documentation and finalised progress bar displayed while model downloads --- napari_organoid_counter/_orgacount.py | 117 +++++++++++++--- napari_organoid_counter/_utils.py | 5 +- napari_organoid_counter/_widget.py | 193 +++++++++++++++----------- napari_organoid_counter/settings.py | 2 +- napari_organoid_counter/test.py | 75 ++++++++++ 5 files changed, 288 insertions(+), 104 deletions(-) create mode 100644 napari_organoid_counter/test.py diff --git a/napari_organoid_counter/_orgacount.py b/napari_organoid_counter/_orgacount.py index b6a555d..e72f129 100644 --- a/napari_organoid_counter/_orgacount.py +++ b/napari_organoid_counter/_orgacount.py @@ -2,7 +2,7 @@ import torch from torchvision.transforms import ToTensor from napari.utils import progress -import subprocess +from urllib.request import urlretrieve from napari_organoid_counter._utils import frcnn, prepare_img, apply_nms, convert_boxes_to_napari_view, convert_boxes_from_napari_view, get_diams, return_is_file from napari_organoid_counter import settings @@ -37,19 +37,16 @@ class OrganoiDL(): next_id: dict Each key will be a set of predictions of the model abd the values will hold the next id to be attributed to a newly added box - ''' - def __init__(self): + def __init__(self, handle_progress): super().__init__() + self.handle_progress = handle_progress self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') self.cur_confidence = 0.05 self.cur_min_diam = 30 self.transfroms = ToTensor() - # create cache dir for models if it doesn't exist - settings.MODELS_DIR.mkdir(parents=True, exist_ok=True) - self.model = None self.img_scale = [0., 0.] self.pred_bboxes = {} @@ -58,31 +55,70 @@ def __init__(self): self.next_id = {} def set_scale(self, img_scale): + ''' Set the image scale: used to calculate real box sizes. ''' self.img_scale = img_scale def set_model(self, model_name): - # initialise model instance + ''' Initialise model instance and load model checkpoint and send to device. ''' self.model = frcnn(num_classes=2, rpn_score_thresh=0, box_score_thresh = self.cur_confidence) - # download model if not there already - if not return_is_file(settings.MODELS_DIR, settings.MODELS[model_name]["filename"]): self.download_model() self.load_model_checkpoint(model_name) self.model = self.model.to(self.device) def download_model(self, model='default'): - ''' Downloads the model from zenodo and returns the path where it is stored ''' - subprocess.run(["zenodo_get", settings.MODELS[model]["source"], "-o", settings.MODELS_DIR]) - + ''' Downloads the model from zenodo and stores it in settings.MODELS_DIR ''' + # specify the url of the file which is to be downloaded + down_url = settings.MODELS[model]["source"] + # specify save location where the file is to be saved + save_loc = os.path.join(str(settings.MODELS_DIR), settings.MODELS[model]["filename"]) + # Downloading using urllib + urlretrieve(down_url,save_loc, self.handle_progress) + def load_model_checkpoint(self, model_name): - ''' Loads the model checkpoint ''' + ''' Loads the model checkpoint for the model specified in model_name ''' model_checkpoint = os.path.join(settings.MODELS_DIR, settings.MODELS[model_name]["filename"]) ckpt = torch.load(model_checkpoint, map_location=self.device) self.model.load_state_dict(ckpt) #.state_dict()) - def sliding_window(self, test_img, step, window_size, rescale_factor, prepadded_height, prepadded_width, pred_bboxes=[], scores_list=[]): - + def sliding_window(self, + test_img, + step, + window_size, + rescale_factor, + prepadded_height, + prepadded_width, + pred_bboxes=[], + scores_list=[]): + ''' Runs sliding window inference and returns predicting bounding boxes and confidence scores for each box. + Inputs + ---------- + test_img: Tensor of size [B, C, H, W] + The image ready to be given to model as input + step: int + The step of the sliding window, same in x and y + window_size: int + The sliding window size, same in x and y + rescale_factor: float + The rescaling factor by which the image has already been resized. Is 1/downsampling + prepadded_height: int + The image height before padding was applied + prepadded_width: int + The image width before padding was applied + pred_bboxes: list of + The + scores_list: list of + The + Outputs + ---------- + pred_bboxes: list of Tensors, default is an empty list + The resulting predicted boxes are appended here - if model is run at different window + sizes and downsampling this list will store results of all runs of the sliding window + so will not be empty the second, third etc. time. + scores_list: list of Tensor, default is an empty list + The resulting confidence scores of the model for the predicted boxes are appended here + Same as pred_bboxes, can be empty on first run but stores results of all runs. + ''' for i in progress(range(0, prepadded_height, step)): for j in progress(range(0, prepadded_width, step)): - # crop img_crop = test_img[:, :, i:(i+window_size), j:(j+window_size)] # get predictions @@ -106,11 +142,24 @@ def run(self, window_sizes, downsampling_sizes, window_overlap): - - # run for all window sizes + ''' Runs inference for an image at multiple window sizes and downsampling rates using sliding window ineference. + The results are filtered using the NMS algorithm and are then stored to dicts. + Inputs + ---------- + img: Numpy array of size [H, W] + The image ready to be given to model as input + shapes_name: str + The name of the new predictions + window_size: list of ints + The sliding window size, same in x and y, if multiple sliding window will run mulitple times + downsampling_sizes: list of ints + The downsampling factor of the image, list size must match window_size + window_overlap: float + The window overlap for the sliding window inference. + ''' bboxes = [] scores = [] - + # run for all window sizes for window_size, downsampling in zip(window_sizes, downsampling_sizes): # compute the step for the sliding window, based on window overlap rescale_factor = 1 / downsampling @@ -118,9 +167,22 @@ def run(self, window_size = round(window_size * rescale_factor) step = round(window_size * window_overlap) # prepare image for model - norm, tensor, etc. - ready_img, prepadded_height, prepadded_width = prepare_img(img, step, window_size, rescale_factor, self.transfroms , self.device) - bboxes, scores = self.sliding_window(ready_img, step, window_size, rescale_factor, prepadded_height, prepadded_width, bboxes, scores) - + ready_img, prepadded_height, prepadded_width = prepare_img(img, + step, + window_size, + rescale_factor, + self.transfroms, + self.device) + # and run sliding window over whole image + bboxes, scores = self.sliding_window(ready_img, + step, + window_size, + rescale_factor, + prepadded_height, + prepadded_width, + bboxes, + scores) + # stack results bboxes = torch.stack(bboxes) scores = torch.stack(scores) # apply NMS to remove overlaping boxes @@ -132,6 +194,8 @@ def run(self, self.next_id[shapes_name] = num_predictions+1 def apply_params(self, shapes_name, confidence, min_diameter_um): + """ After resutls have been stored in dict this function will filter the dicts based on the confidence + and min_diameter_um thresholds for the given results defined by shape_name and return the filtered dicts. """ self.cur_confidence = confidence self.cur_min_diam = min_diameter_um pred_bboxes, pred_scores, pred_ids = self._apply_confidence_thresh(shapes_name) @@ -141,6 +205,7 @@ def apply_params(self, shapes_name, confidence, min_diameter_um): return pred_bboxes, pred_scores, pred_ids def _apply_confidence_thresh(self, shapes_name): + """ Filters out results of shapes_name based on the current confidence threshold. """ if shapes_name not in self.pred_bboxes.keys(): return torch.empty((0)) keep = (self.pred_scores[shapes_name]>self.cur_confidence).nonzero(as_tuple=True)[0] result_bboxes = self.pred_bboxes[shapes_name][keep] @@ -149,6 +214,7 @@ def _apply_confidence_thresh(self, shapes_name): return result_bboxes, result_scores, result_ids def _filter_small_organoids(self, pred_bboxes, pred_scores, pred_ids): + """ Filters out small result boxes of shapes_name based on the current min diameter size. """ if pred_bboxes is None: return None if len(pred_bboxes)==0: return None min_diameter_x = self.cur_min_diam / self.img_scale[0] @@ -163,6 +229,11 @@ def _filter_small_organoids(self, pred_bboxes, pred_scores, pred_ids): return pred_bboxes, pred_scores, pred_ids def update_bboxes_scores(self, shapes_name, new_bboxes, new_scores, new_ids): + ''' Updated the results dicts, self.pred_bboxes, self.pred_scores and self.pred_ids with new results. + If the shapes name doesn't exist as a key in the dicts the results are added with the new key. If the + key exists then new_bboxes, new_scores and new_ids are compared to the class result dicts and the dicts + are updated, either by adding some box (user added box) or removing some box (user deleted a prediction).''' + new_bboxes = convert_boxes_from_napari_view(new_bboxes) new_scores = torch.Tensor(list(new_scores)) new_ids = list(new_ids) @@ -206,11 +277,13 @@ def update_bboxes_scores(self, shapes_name, new_bboxes, new_scores, new_ids): self.pred_ids[shapes_name] = new_pred_ids def update_next_id(self, shapes_name, c=0): + """ Updates the next id to append to result dicts. If input c is given then that will be the next id. """ if c!=0: self.next_id[shapes_name] = c else: self.next_id[shapes_name] += 1 def remove_shape_from_dict(self, shapes_name): + """ Removes results of shapes_name from all result dicts. """ del self.pred_bboxes[shapes_name] del self.pred_scores[shapes_name] del self.pred_ids[shapes_name] diff --git a/napari_organoid_counter/_utils.py b/napari_organoid_counter/_utils.py index cbbd0e2..646eedc 100644 --- a/napari_organoid_counter/_utils.py +++ b/napari_organoid_counter/_utils.py @@ -18,7 +18,9 @@ from napari_organoid_counter import settings -def check_for_local_models(): +def check_for_local_models_and_add(): + """ Checks the models directory for any local models previously added by the user. + If some are found then these are added to the model dictionary (see settings). """ if not os.path.exists(settings.MODELS_DIR): return model_names_in_dir = [file for file in os.listdir(settings.MODELS_DIR)] model_names_in_dict = [settings.MODELS[key]["filename"] for key in settings.MODELS.keys()] @@ -27,6 +29,7 @@ def check_for_local_models(): _ = add_to_dict(model_name) def add_to_dict(filepath): + """ Given the full path and name of a model in filepath the model is added to the models dict (see settings)""" filepath = Path(filepath) name = filepath.name stem_name = filepath.stem diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index 48c268f..62fa243 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -8,51 +8,26 @@ from napari.utils.notifications import show_info from PyQt5.QtCore import Qt -from PyQt5.QtWidgets import (QComboBox, QPushButton, QVBoxLayout, QHBoxLayout, QWidget, QSlider, QLabel, QFileDialog, QLineEdit, QGroupBox, QDialog, QGridLayout) +from PyQt5.QtWidgets import * from napari_organoid_counter._orgacount import OrganoiDL -from napari_organoid_counter._utils import check_for_local_models, add_to_dict, return_is_file, apply_normalization, write_to_csv, get_bbox_diameters, write_to_json, get_bboxes_as_dict, squeeze_img, set_dict_key +from napari_organoid_counter._utils import * from napari_organoid_counter import settings import warnings warnings.filterwarnings("ignore") -class MyInputDialog(QDialog): - def __init__(self, parent: QWidget): - super().__init__(parent) - self.setWindowTitle("Confirm Download") - self.ok_btn = QPushButton("OK") - self.cancel_btn = QPushButton("Cancel") - text = ["Model not found locally. Downloading default model to "+settings.MODELS_DIR+"\n" - "This will only happen once. Click ok to continue or cancel if you do not agree. "] - - layout = QGridLayout() - layout.addWidget(QLabel(text), 0, 0) - layout.addWidget(self.ok_btn, 1, 0) - layout.addWidget(self.cancel_btn, 1, 1) - self.setLayout(layout) - - self.ok_btn.clicked.connect(self.accept) - self.cancel_btn.clicked.connect(self.reject) - - def accept(self) -> None: - self.close() - return - def reject(self) -> None: - self.close() - return - class OrganoidCounterWidget(QWidget): ''' - The widget of the organoid counter + The main widget of the organoid counter Parameters ---------- napari_viewer: string The current napari viewer window_sizes: list of ints, default [1024] A list with the sizes of the windows on which the model will be run. If more than one window_size is given then the model will run on several window sizes and then - combne the results + combine the results downsampling:list of ints, default [2] A list with the sizes of the downsampling ratios for each window size. List size must be the same as the window_sizes list min_diameter: int, default 30 @@ -62,7 +37,7 @@ class OrganoidCounterWidget(QWidget): Attributes ---------- model_name: str - The name of the default model + The name of the model user has selected image_layer_names: list of strings Will hold the names of all the currently open images in the viewer image_layer_name: string @@ -81,7 +56,6 @@ class OrganoidCounterWidget(QWidget): The current number of organoids original_images: dict original_contrast: dict - ''' def __init__(self, napari_viewer, @@ -93,9 +67,15 @@ def __init__(self, # assign class variables self.viewer = napari_viewer + + # create cache dir for models if it doesn't exist and add any previously added local + # models to the model dict settings.init() - check_for_local_models() + settings.MODELS_DIR.mkdir(parents=True, exist_ok=True) + check_for_local_models_and_add() self.model_name = list(settings.MODELS.keys())[0] + + # init params self.window_sizes = window_sizes self.downsampling = downsampling self.min_diameter = min_diameter @@ -107,7 +87,6 @@ def __init__(self, self.save_layer_name = '' self.cur_shapes_name = '' self.cur_shapes_layer = None - self.organoiDL = OrganoiDL() self.num_organoids = 0 self.original_images = {} self.original_contrast = {} @@ -119,6 +98,9 @@ def __init__(self, self.layout().addWidget(self._setup_input_widget()) self.layout().addWidget(self._setup_output_widget()) + # initialise organoidl instance + self.organoiDL = OrganoiDL(self.handle_progress) + # get already opened layers self.image_layer_names = self._get_layer_names() if len(self.image_layer_names)>0: self._update_added_image(self.image_layer_names) @@ -128,11 +110,22 @@ def __init__(self, self.viewer.layers.events.inserted.connect(self._added_layer) self.viewer.layers.events.removed.connect(self._removed_layer) self.viewer.layers.selection.events.changed.connect(self._sel_layer_changed) - - self.diameter_slider_changed = False # used for changing slider and text of min diameter - self.confidence_slider_changed = False # used for changing slider and text of confidence threshold + # setup flags used for changing slider and text of min diameter and confidence threshold + self.diameter_slider_changed = False + self.confidence_slider_changed = False + + def handle_progress(self, blocknum, blocksize, totalsize): + """ When the model is being downloaded, this method is called and th progress of the download + is calculated and displayed on the progress bar. This function was re-implemented from: + https://www.geeksforgeeks.org/pyqt5-how-to-automate-progress-bar-while-downloading-using-urllib/ """ + read_data = blocknum * blocksize # calculate the progress + if totalsize > 0: + download_percentage = read_data * 100 / totalsize + self.progress_bar.setValue(download_percentage) + QApplication.processEvents() def _sel_layer_changed(self, event): + """ Is called whenever the user selects a different layer to work on. """ cur_layer_list = list(self.viewer.layers.selection) if len(cur_layer_list)==0: return cur_seg_selected = cur_layer_list[-1] @@ -164,6 +157,7 @@ def _added_layer(self, event): self.shape_layer_names.extend(new_shape_layer_names) def _removed_layer(self, event): + """ Is called whenever a layer has been deleted (by the user) and removes the layer from GUI and backend. """ new_image_layer_names = self._get_layer_names() new_shape_layer_names = self._get_layer_names(layer_type=layers.Shapes) removed_image_layer_names = [name for name in self.image_layer_names if name not in new_image_layer_names] @@ -218,12 +212,10 @@ def _update_vis_bboxes(self, bboxes, scores, box_ids, labels_layer_name): edge_color='magenta', shape_type='rectangle', edge_width=12) # warning generated here - # set up event handler for when data from this layer changes - + # set current_edge_width so edge width is the same when users annotate - doesnt' fix new preds being added! self.viewer.layers[labels_layer_name].current_edge_width = 12 - def _on_preprocess_click(self): """ Is called whenever preprocess button is clicked """ if not self.image_layer_name: show_info('Please load an image first and try again!') @@ -231,17 +223,24 @@ def _on_preprocess_click(self): def _on_run_click(self): """ Is called whenever Run Organoid Counter button is clicked """ - # check if an image has been loaded if not self.image_layer_name: show_info('Please load an image first and try again!') return - # check if model has been loaded and scale set + # check if model exists locally and if not ask user if it's ok to download if not return_is_file(settings.MODELS_DIR, settings.MODELS[self.model_name]["filename"]): - ww = MyInputDialog(self) - ww.exec_() - - self.organoiDL.set_model(model_name=self.model_name) + confirm_window = ConfirmUpload(self) + confirm_window.exec_() + # if user clicks cancel return doing nothing + if confirm_window.result() != QDialog.Accepted: return + # otherwise donwload model and display progress in progress bar + else: + self.progress_box.show() + self.organoiDL.download_model(self.model_name) + self.progress_box.hide() + + # load model checkpoint + self.organoiDL.set_model(self.model_name) if self.organoiDL.img_scale[0]==0: self.organoiDL.set_scale(self.viewer.layers[self.image_layer_name].scale) # make sure the number of windows and downsamplings are the same @@ -285,6 +284,7 @@ def _on_run_click(self): self._preprocess() def _on_model_selection_changed(self): + """ Is called when user selects a new model from the dropdown menu. """ self.model_name = self.model_selection.currentText() def _on_choose_model_clicked(self): @@ -299,7 +299,6 @@ def _on_choose_model_clicked(self): model_name = add_to_dict(model_path) self.model_selection.addItem(model_name) - def _on_window_sizes_changed(self): """ Is called whenever user changes the window sizes text box """ new_window_sizes = self.window_sizes_textbox.text() @@ -415,7 +414,6 @@ def _on_save_csv_click(self): name, _ = fd.getSaveFileName(self, 'Save File', self.save_layer_name, 'CSV files (*.csv)')#, 'CSV Files (*.csv)') if name: write_to_csv(name, data_csv) - def _on_save_json_click(self): """ Is called whenever Save boxes button is clicked """ bboxes = self.viewer.layers[self.save_layer_name].data @@ -529,15 +527,17 @@ def _setup_input_widget(self): window_sizes_box = self._setup_window_sizes_box() downsampling_box = self._setup_downsampling_box() run_box = self._setup_run_box() + self._setup_progress_box() + # and add all these to the layout input_widget = QGroupBox('Input configurations') vbox = QVBoxLayout() - #vbox.addWidget(self.input_box) vbox.addLayout(input_box) vbox.addLayout(model_box) vbox.addLayout(window_sizes_box) vbox.addLayout(downsampling_box) vbox.addLayout(run_box) + vbox.addWidget(self.progress_box) input_widget.setLayout(vbox) return input_widget @@ -556,6 +556,7 @@ def _setup_output_widget(self): vbox.addWidget(self.organoid_number_label) vbox.addLayout(self._setup_reset_box()) vbox.addLayout(self._setup_save_box()) + output_widget.setLayout(vbox) return output_widget @@ -581,20 +582,18 @@ def _setup_input_box(self): hbox.addWidget(image_label, 2) hbox.addWidget(self.image_layer_selection, 4) hbox.addWidget(preprocess_btn, 4) - #self.input_box.setLayout(hbox) - #self.input_box.setStyleSheet("border: 0px") return hbox def _setup_model_box(self): """ - Sets up the GUI part where the model path is set + Sets up the GUI part where the model is selected from a drop down menu. """ hbox = QHBoxLayout() # setup the label model_label = QLabel('Model: ', self) model_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) - # set up the browse files button + # setup the browse files button fileOpenButton = QPushButton('Add custom model', self) fileOpenButton.show() fileOpenButton.clicked.connect(self._on_choose_model_clicked) @@ -637,8 +636,7 @@ def _setup_window_sizes_box(self): #self.window_sizes_box.setLayout(hbox) #self.window_sizes_box.setStyleSheet("border: 0px") return hbox - - + def _setup_downsampling_box(self): """ Sets up the GUI part where the downsampling parameters are set @@ -681,22 +679,37 @@ def _setup_run_box(self): hbox.addStretch(1) return hbox + def _setup_progress_box(self): + """ + Sets up the GUI part which appears when the model is being downloaded. + This should only happen once for each model whihc is then stored in cache. + """ + self.progress_box = QGroupBox() + hbox = QHBoxLayout() + download_label = QLabel('Downloading model progress: ', self) + download_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) + self.progress_bar = QProgressBar(self) # creating progress bar + hbox.addWidget(download_label) + hbox.addWidget(self.progress_bar) + self.progress_box.setLayout(hbox) + self.progress_box.hide() + def _setup_min_diameter_box(self): """ Sets up the GUI part where the minimum diameter parameter is displayed """ hbox = QHBoxLayout() - # set up the min diameter slider + # setup the min diameter slider self.min_diameter_slider = QSlider(Qt.Horizontal) self.min_diameter_slider.setMinimum(10) self.min_diameter_slider.setMaximum(100) self.min_diameter_slider.setSingleStep(10) self.min_diameter_slider.setValue(self.min_diameter) self.min_diameter_slider.valueChanged.connect(self._on_diameter_slider_changed) - # set up the label + # setup the label min_diameter_label = QLabel('Minimum Diameter [um]: ', self) min_diameter_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) - # set up text box + # setup text box self.min_diameter_textbox = QLineEdit(self) self.min_diameter_textbox.setText(str(self.min_diameter)) self.min_diameter_textbox.returnPressed.connect(self._on_diameter_textbox_changed) @@ -711,7 +724,7 @@ def _setup_confidence_box(self): Sets up the GUI part where the confidence parameter is displayed """ hbox = QHBoxLayout() - # set up confidence slider + # setup confidence slider self.confidence_slider = QSlider(Qt.Horizontal) self.confidence_slider.setMinimum(5) self.confidence_slider.setMaximum(100) @@ -719,10 +732,10 @@ def _setup_confidence_box(self): vis_confidence = int(self.confidence*100) self.confidence_slider.setValue(vis_confidence) self.confidence_slider.valueChanged.connect(self._on_confidence_slider_changed) - # set up label + # setup label confidence_label = QLabel('Model confidence: ', self) confidence_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) - # set up text box + # setup text box self.confidence_textbox = QLineEdit(self) self.confidence_textbox.setText(str(self.confidence)) self.confidence_textbox.returnPressed.connect(self._on_confidence_textbox_changed) @@ -732,30 +745,16 @@ def _setup_confidence_box(self): hbox.addWidget(self.confidence_slider, 6) return hbox - ''' - def _setup_display_res_box(self): - - self.display_res_box = QGroupBox() - hbox = QHBoxLayout() - - self.organoid_number_label = QLabel('Number of organoids: 0', self) - self.organoid_number_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) - - hbox.addWidget(self.organoid_number_label) - self.display_res_box.setLayout(hbox) - self.display_res_box.setStyleSheet("border: 0px") - ''' - def _setup_reset_box(self): """ Sets up the GUI part where screenshot and reset are available to the user """ #self.reset_box = QGroupBox() hbox = QHBoxLayout() - # set up button for resetting parameters + # setup button for resetting parameters self.reset_btn = QPushButton("Reset Configs") self.reset_btn.clicked.connect(self._on_reset_click) - # set up button for taking screenshot of current viewer + # setup button for taking screenshot of current viewer self.screenshot_btn = QPushButton("Take screenshot") self.screenshot_btn.clicked.connect(self._on_screenshot_click) # and add all these to the layout @@ -774,16 +773,16 @@ def _setup_save_box(self): """ #self.save_box = QGroupBox() hbox = QHBoxLayout() - # set up button for saving features + # setup button for saving features self.save_csv_btn = QPushButton("Save features") self.save_csv_btn.clicked.connect(self._on_save_csv_click) - # set up button for saving boxes + # setup button for saving boxes self.save_json_btn = QPushButton("Save boxes") self.save_json_btn.clicked.connect(self._on_save_json_click) - # set up label + # setup label self.save_label = QLabel('Save: ', self) self.save_label.setAlignment(Qt.AlignCenter | Qt.AlignVCenter) - # set up drop down option for selecting which shapes layer to save + # setup drop down option for selecting which shapes layer to save self.output_layer_selection = QComboBox() if self.shape_layer_names is not None: for name in self.shape_layer_names: self.output_layer_selection.addItem(name) @@ -806,3 +805,37 @@ def _get_layer_names(self, layer_type: layers.Layer = layers.Image) -> List[str] if layer_names: return [] + layer_names else: return [] + +class ConfirmUpload(QDialog): + ''' + The QDialog box that appears when the user selects to run organoid counter + without having the selected model locally + Parameters + ---------- + parent: QWidget + The parent widget, in this case an instance of OrganoidCounterWidget + + ''' + def __init__(self, parent: QWidget): + super().__init__(parent) + + self.setWindowTitle("Confirm Download") + # setup buttons and text to be displayed + ok_btn = QPushButton("OK") + cancel_btn = QPushButton("Cancel") + text = ("Model not found locally. Downloading default model to \n" + +str(settings.MODELS_DIR)+"\n" + "This will only happen once. Click ok to continue or \n" + "cancel if you do not agree. You won't be able to run\n" + "the organoid counter if you click cancel.") + # add all to layout + layout = QVBoxLayout() + layout.addWidget(QLabel(text)) + hbox = QHBoxLayout() + hbox.addWidget(ok_btn) + hbox.addWidget(cancel_btn) + layout.addLayout(hbox) + self.setLayout(layout) + # connect ok and cancel buttons with accept and reject signals + ok_btn.clicked.connect(self.accept) + cancel_btn.clicked.connect(self.reject) \ No newline at end of file diff --git a/napari_organoid_counter/settings.py b/napari_organoid_counter/settings.py index f6b1fbc..94c6327 100644 --- a/napari_organoid_counter/settings.py +++ b/napari_organoid_counter/settings.py @@ -4,7 +4,7 @@ def init(): global MODELS MODELS = { - "default": {"filename": "model_v1.ckpt", "source": "10.5281/zenodo.7708763"} + "default": {"filename": "model_v1.ckpt", "source": "https://zenodo.org/record/7708763/files/model_v1.ckpt"} } global MODELS_DIR diff --git a/napari_organoid_counter/test.py b/napari_organoid_counter/test.py new file mode 100644 index 0000000..ed0cce1 --- /dev/null +++ b/napari_organoid_counter/test.py @@ -0,0 +1,75 @@ +# importing libraries +import urllib.request +from PyQt5.QtWidgets import * +import sys + +class GeeksforGeeks(QWidget): + + def __init__(self): + super().__init__() + + # calling a defined method to initialize UI + self.init_UI() + + # method for creating UI widgets + def init_UI(self): + + # creating progress bar + self.progressBar = QProgressBar(self) + + # setting its size + self.progressBar.setGeometry(25, 45, 210, 30) + + # creating push button to start download + self.button = QPushButton('Start', self) + + # assigning position to button + self.button.move(50, 100) + + # assigning activity to push button + self.button.clicked.connect(self.Download) + + # setting window geometry + self.setGeometry(310, 310, 280, 170) + + # setting window action + self.setWindowTitle("GeeksforGeeks") + + # showing all the widgets + self.show() + + # when push button is pressed, this method is called + def Handle_Progress(self, blocknum, blocksize, totalsize): + + ## calculate the progress + readed_data = blocknum * blocksize + + if totalsize > 0: + download_percentage = readed_data * 100 / totalsize + self.progressBar.setValue(download_percentage) + QApplication.processEvents() + + # method to download any file using urllib + def Download(self): + + # specify the url of the file which is to be downloaded + down_url = 'https://zenodo.org/record/7708763/files/model_v1.ckpt' # specify download url here + + # specify save location where the file is to be saved + save_loc = '/Users/christina.bukas/Desktop/model_v1.ckpt' + # Downloading using urllib + urllib.request.urlretrieve(down_url,save_loc, self.Handle_Progress) + + +# main method to call our app +if __name__ == '__main__': + + # create app + App = QApplication(sys.argv) + + # create the instance of our window + window = GeeksforGeeks() + + # start the app + sys.exit(App.exec()) + From 86691351ccafe152a0b877d9087e3d3e0234d2bc Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Thu, 13 Jul 2023 09:36:32 +0200 Subject: [PATCH 11/23] changed test to run faster --- napari_organoid_counter/_tests/test_widget.py | 5 ++++- napari_organoid_counter/_widget.py | 4 +++- 2 files changed, 7 insertions(+), 2 deletions(-) diff --git a/napari_organoid_counter/_tests/test_widget.py b/napari_organoid_counter/_tests/test_widget.py index 614f747..30f76a1 100644 --- a/napari_organoid_counter/_tests/test_widget.py +++ b/napari_organoid_counter/_tests/test_widget.py @@ -20,7 +20,10 @@ def test_organoid_counter_widget(make_napari_viewer, capsys): viewer.add_image(test_img, name='Test') # create our widget, passing in the viewer - my_widget = OrganoidCounterWidget(viewer) + my_widget = OrganoidCounterWidget(viewer, + window_sizes=[500], + downsampling=[2], + window_overlap=1) # call preprocessing - remove duplicate here? my_widget._preprocess() diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index 62fa243..6b63cf8 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -61,6 +61,7 @@ def __init__(self, napari_viewer, window_sizes: List = [1024], downsampling: List = [2], + window_overlap: float = 0.5, min_diameter: int = 30, confidence: float = 0.8): super().__init__() @@ -78,6 +79,7 @@ def __init__(self, # init params self.window_sizes = window_sizes self.downsampling = downsampling + self.window_overlap = window_overlap self.min_diameter = min_diameter self.confidence = confidence @@ -270,7 +272,7 @@ def _on_run_click(self): labels_layer_name, self.window_sizes, self.downsampling, - window_overlap = 0.5) + self.window_overlap) # set the confidence threshold, remove small organoids and get bboxes in format o visualise bboxes, scores, box_ids = self.organoiDL.apply_params(labels_layer_name, self.confidence, self.min_diameter) From a5ca4c8d7df352d724a813fb9f3323184a71f87e Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Fri, 14 Jul 2023 10:59:29 +0200 Subject: [PATCH 12/23] removed extra file --- napari_organoid_counter/test.py | 75 --------------------------------- 1 file changed, 75 deletions(-) delete mode 100644 napari_organoid_counter/test.py diff --git a/napari_organoid_counter/test.py b/napari_organoid_counter/test.py deleted file mode 100644 index ed0cce1..0000000 --- a/napari_organoid_counter/test.py +++ /dev/null @@ -1,75 +0,0 @@ -# importing libraries -import urllib.request -from PyQt5.QtWidgets import * -import sys - -class GeeksforGeeks(QWidget): - - def __init__(self): - super().__init__() - - # calling a defined method to initialize UI - self.init_UI() - - # method for creating UI widgets - def init_UI(self): - - # creating progress bar - self.progressBar = QProgressBar(self) - - # setting its size - self.progressBar.setGeometry(25, 45, 210, 30) - - # creating push button to start download - self.button = QPushButton('Start', self) - - # assigning position to button - self.button.move(50, 100) - - # assigning activity to push button - self.button.clicked.connect(self.Download) - - # setting window geometry - self.setGeometry(310, 310, 280, 170) - - # setting window action - self.setWindowTitle("GeeksforGeeks") - - # showing all the widgets - self.show() - - # when push button is pressed, this method is called - def Handle_Progress(self, blocknum, blocksize, totalsize): - - ## calculate the progress - readed_data = blocknum * blocksize - - if totalsize > 0: - download_percentage = readed_data * 100 / totalsize - self.progressBar.setValue(download_percentage) - QApplication.processEvents() - - # method to download any file using urllib - def Download(self): - - # specify the url of the file which is to be downloaded - down_url = 'https://zenodo.org/record/7708763/files/model_v1.ckpt' # specify download url here - - # specify save location where the file is to be saved - save_loc = '/Users/christina.bukas/Desktop/model_v1.ckpt' - # Downloading using urllib - urllib.request.urlretrieve(down_url,save_loc, self.Handle_Progress) - - -# main method to call our app -if __name__ == '__main__': - - # create app - App = QApplication(sys.argv) - - # create the instance of our window - window = GeeksforGeeks() - - # start the app - sys.exit(App.exec()) - From 6300b5754a66ed27b04570db3ce0c812d2b01654 Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Fri, 14 Jul 2023 11:01:22 +0200 Subject: [PATCH 13/23] adding instructions on how to install on windows --- .../How to install on a Windows machine.pdf | Bin 0 -> 577271 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 readme-content/How to install on a Windows machine.pdf diff --git a/readme-content/How to install on a Windows machine.pdf b/readme-content/How to install on a Windows machine.pdf new file mode 100644 index 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Date: Fri, 14 Jul 2023 11:52:50 +0200 Subject: [PATCH 14/23] fixed typos, removed os dependencies, changed function name in utils --- napari_organoid_counter/_orgacount.py | 20 ++++++++++---------- napari_organoid_counter/_utils.py | 8 ++++++-- napari_organoid_counter/_widget.py | 3 +-- 3 files changed, 17 insertions(+), 14 deletions(-) diff --git a/napari_organoid_counter/_orgacount.py b/napari_organoid_counter/_orgacount.py index e72f129..8425309 100644 --- a/napari_organoid_counter/_orgacount.py +++ b/napari_organoid_counter/_orgacount.py @@ -1,10 +1,10 @@ -import os import torch from torchvision.transforms import ToTensor -from napari.utils import progress + from urllib.request import urlretrieve +from napari.utils import progress -from napari_organoid_counter._utils import frcnn, prepare_img, apply_nms, convert_boxes_to_napari_view, convert_boxes_from_napari_view, get_diams, return_is_file +from napari_organoid_counter._utils import * from napari_organoid_counter import settings @@ -24,18 +24,18 @@ class OrganoiDL(): model: frcnn The Faster R-CNN model img_scale: list of floats - A list holiding the image resolution in x and y + A list holding the image resolution in x and y pred_bboxes: dict Each key will be a set of predictions of the model, either past or current, and values will be the numpy arrays holding the predicted bounding boxes pred_scores: dict - Each key will be a set of predictions of the model abd the values will hold the confidence of the model for each + Each key will be a set of predictions of the model and the values will hold the confidence of the model for each predicted bounding box pred_ids: dict - Each key will be a set of predictions of the model abd the values will hold the box id for each + Each key will be a set of predictions of the model and the values will hold the box id for each predicted bounding box next_id: dict - Each key will be a set of predictions of the model abd the values will hold the next id to be attributed to a + Each key will be a set of predictions of the model and the values will hold the next id to be attributed to a newly added box ''' def __init__(self, handle_progress): @@ -69,13 +69,13 @@ def download_model(self, model='default'): # specify the url of the file which is to be downloaded down_url = settings.MODELS[model]["source"] # specify save location where the file is to be saved - save_loc = os.path.join(str(settings.MODELS_DIR), settings.MODELS[model]["filename"]) + save_loc = join_paths(str(settings.MODELS_DIR), settings.MODELS[model]["filename"]) # Downloading using urllib urlretrieve(down_url,save_loc, self.handle_progress) def load_model_checkpoint(self, model_name): ''' Loads the model checkpoint for the model specified in model_name ''' - model_checkpoint = os.path.join(settings.MODELS_DIR, settings.MODELS[model_name]["filename"]) + model_checkpoint = join_paths(settings.MODELS_DIR, settings.MODELS[model_name]["filename"]) ckpt = torch.load(model_checkpoint, map_location=self.device) self.model.load_state_dict(ckpt) #.state_dict()) @@ -194,7 +194,7 @@ def run(self, self.next_id[shapes_name] = num_predictions+1 def apply_params(self, shapes_name, confidence, min_diameter_um): - """ After resutls have been stored in dict this function will filter the dicts based on the confidence + """ After results have been stored in dict this function will filter the dicts based on the confidence and min_diameter_um thresholds for the given results defined by shape_name and return the filtered dicts. """ self.cur_confidence = confidence self.cur_min_diam = min_diameter_um diff --git a/napari_organoid_counter/_utils.py b/napari_organoid_counter/_utils.py index 646eedc..c2cc49e 100644 --- a/napari_organoid_counter/_utils.py +++ b/napari_organoid_counter/_utils.py @@ -18,7 +18,7 @@ from napari_organoid_counter import settings -def check_for_local_models_and_add(): +def add_local_models(): """ Checks the models directory for any local models previously added by the user. If some are found then these are added to the model dictionary (see settings). """ if not os.path.exists(settings.MODELS_DIR): return @@ -38,9 +38,13 @@ def add_to_dict(filepath): def return_is_file(path, filename): """ Return True if the file exists in path and False otherwise """ - full_path = os.path.join(path, filename) + full_path = join_paths(path, filename) return os.path.isfile(full_path) +def join_paths(path1, path2): + """ Returns output of os.path.join """ + return os.path.join(path1, path2) + @contextmanager def set_dict_key(dictionary, key, value): """ Used to set a new value in the napari layer metadata """ diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index 62fa243..4a1ea12 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -1,4 +1,3 @@ -import os from typing import List from skimage.io import imsave @@ -72,7 +71,7 @@ def __init__(self, # models to the model dict settings.init() settings.MODELS_DIR.mkdir(parents=True, exist_ok=True) - check_for_local_models_and_add() + add_local_models() self.model_name = list(settings.MODELS.keys())[0] # init params From 89f3e5b3a0b3aa066e13c57de61e8604292c6ad4 Mon Sep 17 00:00:00 2001 From: Christina Bukas <31160776+christinab12@users.noreply.github.com> Date: Fri, 14 Jul 2023 13:22:59 +0200 Subject: [PATCH 15/23] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e82bf7e..c2e5506 100644 --- a/README.md +++ b/README.md @@ -41,7 +41,7 @@ Then run napari on your terminal. Checkout our *What's New in v2* [here](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/.napari/DESCRIPTION.md#whats-new-in-v2). ## How to use? -After installing, you can type ```napari``` in your terminal and select the plugin from the drop down menu. +After installing, you can start napri (either by typing ```napari``` in your terminal or by launching the application) and select the plugin from the drop down menu. For more information on this plugin, its' intended audience, as well as Quickstart guide go to our [Quickstart guide](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/.napari/DESCRIPTION.md#quickstart). From 727777863e3cfac7d2c0bdd295801192a613ea03 Mon Sep 17 00:00:00 2001 From: Christina Bukas <31160776+christinab12@users.noreply.github.com> Date: Fri, 14 Jul 2023 13:23:42 +0200 Subject: [PATCH 16/23] Update DESCRIPTION.md --- .napari/DESCRIPTION.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.napari/DESCRIPTION.md b/.napari/DESCRIPTION.md index 760ea5b..e9869c1 100644 --- a/.napari/DESCRIPTION.md +++ b/.napari/DESCRIPTION.md @@ -32,6 +32,8 @@ To install latest development version : ## Quickstart +After installation, you can start napari (either by typing ```napari``` in your terminal or by launching the application) and select the plugin from the drop down menu. + The use of the napari-organoid-counter plugin is straightforward. Here is a step-to-step guide of the standard workflow: 1. You can load the image or images you wish to process into the napari viewer with a simple drag and drop 2. You can then select the layer you wish to work on by the drop-down box at the top of the input configurations From 7c8c8624ef53f1392bec0cb8ffe08a091a46efc0 Mon Sep 17 00:00:00 2001 From: Christina Bukas <31160776+christinab12@users.noreply.github.com> Date: Fri, 14 Jul 2023 13:23:58 +0200 Subject: [PATCH 17/23] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c2e5506..bbe1690 100644 --- a/README.md +++ b/README.md @@ -41,7 +41,7 @@ Then run napari on your terminal. Checkout our *What's New in v2* [here](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/.napari/DESCRIPTION.md#whats-new-in-v2). ## How to use? -After installing, you can start napri (either by typing ```napari``` in your terminal or by launching the application) and select the plugin from the drop down menu. +After installing, you can start napari (either by typing ```napari``` in your terminal or by launching the application) and select the plugin from the drop down menu. For more information on this plugin, its' intended audience, as well as Quickstart guide go to our [Quickstart guide](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/.napari/DESCRIPTION.md#quickstart). From ecddb1fae40f0c8d93038b6e370941ee44c365e5 Mon Sep 17 00:00:00 2001 From: Christina Bukas <31160776+christinab12@users.noreply.github.com> Date: Fri, 14 Jul 2023 15:22:08 +0200 Subject: [PATCH 18/23] Update DESCRIPTION.md --- .napari/DESCRIPTION.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.napari/DESCRIPTION.md b/.napari/DESCRIPTION.md index e9869c1..3ca73c6 100644 --- a/.napari/DESCRIPTION.md +++ b/.napari/DESCRIPTION.md @@ -28,7 +28,8 @@ You can install `napari-organoid-counter` via [pip](https://pypi.org/project/nap To install latest development version : pip install git+https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter.git - + +For installing on a Windows machine via napari, follow the instuctions [here](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/readme-content/How%20to%20install%20on%20a%20Windows%20machine.pdf). ## Quickstart From 169d3f84686a62f43dc0608a9e647205e89cec78 Mon Sep 17 00:00:00 2001 From: Christina Bukas <31160776+christinab12@users.noreply.github.com> Date: Fri, 14 Jul 2023 15:22:38 +0200 Subject: [PATCH 19/23] Update README.md --- README.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/README.md b/README.md index bbe1690..a980892 100644 --- a/README.md +++ b/README.md @@ -34,8 +34,7 @@ For the dev branch you can clone this repo and install with: pip install -e . -Then run napari on your terminal. - +For installing on a Windows machine via napari, follow the instuctions [here](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/readme-content/How%20to%20install%20on%20a%20Windows%20machine.pdf). ## What's new in v2? Checkout our *What's New in v2* [here](https://github.com/HelmholtzAI-Consultants-Munich/napari-organoid-counter/blob/main/.napari/DESCRIPTION.md#whats-new-in-v2). From 1d7b0538ed6293f5c712345310d07ae0ccc830e6 Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Fri, 14 Jul 2023 15:47:47 +0200 Subject: [PATCH 20/23] added new model --- napari_organoid_counter/settings.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/napari_organoid_counter/settings.py b/napari_organoid_counter/settings.py index 94c6327..b715ff3 100644 --- a/napari_organoid_counter/settings.py +++ b/napari_organoid_counter/settings.py @@ -4,7 +4,8 @@ def init(): global MODELS MODELS = { - "default": {"filename": "model_v1.ckpt", "source": "https://zenodo.org/record/7708763/files/model_v1.ckpt"} + "model_1 (default)": {"filename": "model_v1.ckpt", "source": "https://zenodo.org/record/7708763/files/model_v1.ckpt"}, + "model_2": {"filename": "model_v2.ckpt", "source": "https://zenodo.org/record/8146857/files/model_v2.ckpt"}, } global MODELS_DIR From 842695552dece7bd78cc7ef8a70a3c5831ccb80e Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Fri, 14 Jul 2023 15:48:00 +0200 Subject: [PATCH 21/23] fixed by in case 0 organoids found --- napari_organoid_counter/_widget.py | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index 6499436..bb44713 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -197,7 +197,8 @@ def _update_vis_bboxes(self, bboxes, scores, box_ids, labels_layer_name): else: # if no organoids were found just make an empty shapes layer if self.num_organoids==0: - self.cur_shapes_layer = self.viewer.add_shapes(name=labels_layer_name) + self.cur_shapes_layer = self.viewer.add_shapes(name=labels_layer_name, + properties={'box_id': [],'scores': []}) # otherwise make the layer and add the boxes else: properties = {'box_id': box_ids,'scores': scores} @@ -205,14 +206,14 @@ def _update_vis_bboxes(self, bboxes, scores, box_ids, labels_layer_name): 'size': 12, 'anchor': 'upper_left',} self.cur_shapes_layer = self.viewer.add_shapes(bboxes, - name=labels_layer_name, - scale=self.viewer.layers[self.image_layer_name].scale, - face_color='transparent', - properties = properties, - text = text_params, - edge_color='magenta', - shape_type='rectangle', - edge_width=12) # warning generated here + name=labels_layer_name, + scale=self.viewer.layers[self.image_layer_name].scale, + face_color='transparent', + properties = properties, + text = text_params, + edge_color='magenta', + shape_type='rectangle', + edge_width=12) # warning generated here # set current_edge_width so edge width is the same when users annotate - doesnt' fix new preds being added! self.viewer.layers[labels_layer_name].current_edge_width = 12 From 39f2fd127b01bb1001cc4ad4b4a8f99fa1adc2f8 Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Mon, 17 Jul 2023 20:42:22 +0200 Subject: [PATCH 22/23] added download in test --- napari_organoid_counter/_tests/test_widget.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/napari_organoid_counter/_tests/test_widget.py b/napari_organoid_counter/_tests/test_widget.py index 30f76a1..75ec29a 100644 --- a/napari_organoid_counter/_tests/test_widget.py +++ b/napari_organoid_counter/_tests/test_widget.py @@ -37,12 +37,13 @@ def test_organoid_counter_widget(make_napari_viewer, capsys): assert np.min(img) >= 0. # test that organoid counting algorithm has run and new layer with res has been added to viewer + my_widget.organoiDL.download_model(my_widget.model_name) my_widget._on_run_click() layer_names = [layer.name for layer in my_widget.viewer.layers] assert 'Labels-Test' in layer_names # test that class attributes are updated when user changes values from GUI - my_widget._on_diameter_changed() + my_widget._on_diameter_slider_changed() assert my_widget.min_diameter == my_widget.min_diameter_slider.value() my_widget._on_image_selection_changed() From 6b211962c4a117f35a0546ab54ef5c3045f1a07c Mon Sep 17 00:00:00 2001 From: Christina Bukas Date: Mon, 17 Jul 2023 21:03:08 +0200 Subject: [PATCH 23/23] changed progress bar update value to int --- napari_organoid_counter/_widget.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/napari_organoid_counter/_widget.py b/napari_organoid_counter/_widget.py index bb44713..3162baf 100644 --- a/napari_organoid_counter/_widget.py +++ b/napari_organoid_counter/_widget.py @@ -122,7 +122,7 @@ def handle_progress(self, blocknum, blocksize, totalsize): read_data = blocknum * blocksize # calculate the progress if totalsize > 0: download_percentage = read_data * 100 / totalsize - self.progress_bar.setValue(download_percentage) + self.progress_bar.setValue(int(download_percentage)) QApplication.processEvents() def _sel_layer_changed(self, event):