Merge pull request #1 from gbr1/foxy-dev

0.0.2 -  added vision_msgs

README.md

@@ -1,8 +1,25 @@
 # edgeimpulse_ros
-ROS2 wrapper for Edge Impulse 
 
+ROS2 wrapper for Edge Impulse on Linux.
 
-## How to install
+
+## 1. Topics
+
+- `/detection/input/image`, image topic to analyze
+- `/detection/output/image`, image with bounding boxes
+- `/detection/output/info`, VisionInfo message
+- `/detection/output/results`, results as text
+
+## 2. Parameters
+
+- `frame_id` (**string**), _"base_link"_, frame id of output topics
+- `model.filepath` (**string**), _""_, absolute filepath to .eim file
+- `show.overlay` (**bool**), _true_, show bounding boxes on output image
+- `show.labels` (**bool**), _true_, show labels on bounding boxes,
+- `show.classification_info` (**bool**), _true_, show the attendibility (0-1) of the prediction
+
+
+## 3. How to install
 
 1. install edge_impulse_linux: <br>
     `pip3 install edge_impulse_linux`
@@ -30,12 +47,23 @@ ROS2 wrapper for Edge Impulse
     `source install/setup.bash` <br>
 
 
-## How to run
+## 4.  How to run
 
 Launch the node: <br>
     `ros2 run edgeimpulse_ros image_classification --ros-args -p model.filepath:="</absolute/path/to/your/eim/file.eim>" -r /detection/input/image:="/your_image_topic"`
 ` <br>
 
+## 5. Models
+
+Here you find some prebuilt models: [https://github.com/gbr1/edgeimpulse_example_models](https://github.com/gbr1/edgeimpulse_example_models)
+
+## 6. Known issues
+
+- this wrapper works on foxy, galactic and humble are coming soon (incompatibility on vision msgs by ros-perception)
+- if you use a classification model, topic results is empty
+- you cannot change color of bounding boxes (coming soon)
+- other types (imu and sound based ml) are unavailable
+
 
 
 ***Copyright © 2022 Giovanni di Dio Bruno - gbr1.github.io***

edgeimpulse_ros/image_classification.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 
+from distutils.log import info
 from unittest import result
 from .submodules import device_patches
 import cv2
@@ -24,8 +25,10 @@
 
 from sensor_msgs.msg import Image
 
-#from vision_msgs.msg import BoundingBox2DArray
-#from vision_msgs.msg import VisionInfo
+from vision_msgs.msg import Detection2DArray
+from vision_msgs.msg import Detection2D
+from vision_msgs.msg import ObjectHypothesisWithPose
+from vision_msgs.msg import VisionInfo
 
 import os
 import time
@@ -35,31 +38,46 @@
 
 
 
+
 class EI_Image_node(Node):
+
     def __init__(self):
 
         self.occupied = False
         self.img = None
+        self.info_msg = VisionInfo()
         self.cv_bridge = CvBridge()
 
         super().__init__('ei_image_classifier_node')
         self.init_parameters()
         self.ei_classifier = self.EI_Classifier(self.modelfile, self.get_logger())
-        #self.publisher = self.create_publisher(BoundingBox2DArray,'/edge_impulse/detection',1)
+
+        self.info_msg.header.frame_id = self.frame_id
+        self.info_msg.method = self.ei_classifier.model_info['model_parameters']['model_type']
+        self.info_msg.database_location = self.ei_classifier.model_info['project']['name']+' / '+self.ei_classifier.model_info['project']['owner']
+        self.info_msg.database_version = self.ei_classifier.model_info['project']['deploy_version']
 
         self.timer_parameter = self.create_timer(2,self.parameters_callback)
 
         self.image_publisher = self.create_publisher(Image,'/detection/output/image',1)
+        self.results_publisher = self.create_publisher(Detection2DArray,'/detection/output/results',1)
+        self.info_publisher = self.create_publisher(VisionInfo, '/detection/output/info',1)
+
         self.timer_classify = self.create_timer(0.01,self.classify_callback)
         self.timer_classify.cancel()
         self.subscription = self.create_subscription(Image,'/detection/input/image',self.listener_callback,1)
         self.subscription 
 
-
+
+
+
     def init_parameters(self):
         self.declare_parameter('model.filepath','')
         self.modelfile= self.get_parameter('model.filepath').get_parameter_value().string_value
 
+        self.declare_parameter('frame_id','base_link')
+        self.frame_id= self.get_parameter('frame_id').get_parameter_value().string_value
+
         self.declare_parameter('show.overlay', True)
         self.show_overlay = self.get_parameter('show.overlay').get_parameter_value().bool_value
 
@@ -72,9 +90,6 @@ def init_parameters(self):
 
 
 
-
-
-
     def parameters_callback(self):
         self.show_labels_on_image = self.get_parameter('show.labels').get_parameter_value().bool_value
         self.show_extra_classification_info = self.get_parameter('show.classification_info').get_parameter_value().bool_value
@@ -91,13 +106,25 @@ def listener_callback(self, msg):
                 self.img = current_frame
                 self.timer_classify.reset()
 
+
+
+
+
     def classify_callback(self):
         self.occupied = True
+
+        # vision msgs
+        results_msg = Detection2DArray()
+        time_now = self.get_clock().now().to_msg()
+        results_msg.header.stamp = time_now
+        results_msg.header.frame_id = self.frame_id
+
 
         # classify
         features, cropped, res = self.ei_classifier.classify(self.img)
 
-        #prepare output
+
+        #p repare output
         if "classification" in res["result"].keys():
             if self.show_extra_classification_info:
                 self.get_logger().info('Result (%d ms.) ' % (res['timing']['dsp'] + res['timing']['classification']), end='')
@@ -112,6 +139,28 @@ def classify_callback(self):
                 self.get_logger().info('Found %d bounding boxes (%d ms.)' % (len(res["result"]["bounding_boxes"]), res['timing']['dsp'] + res['timing']['classification']))
 
             for bb in res["result"]["bounding_boxes"]:
+                result_msg = Detection2D()
+                result_msg.header.stamp = time_now
+                result_msg.header.frame_id = self.frame_id
+
+                # object with hypthothesis
+                obj_hyp = ObjectHypothesisWithPose()
+                obj_hyp.id = bb['label'] #str(self.ei_classifier.labels.index(bb['label']))
+                obj_hyp.score = bb['value']
+                obj_hyp.pose.pose.position.x = float(bb['x'])
+                obj_hyp.pose.pose.position.y = float(bb['y'])
+                result_msg.results.append(obj_hyp)
+
+                # bounding box
+                result_msg.bbox.center.x = float(bb['x'])
+                result_msg.bbox.center.y = float(bb['y'])
+                result_msg.bbox.size_x = float(bb['width'])
+                result_msg.bbox.size_y = float(bb['height'])
+
+
+                results_msg.detections.append(result_msg)
+
+                # image
                 if self.show_extra_classification_info:
                     self.get_logger().info('%s (%.2f): x=%d y=%d w=%d h=%d' % (bb['label'], bb['value'], bb['x'], bb['y'], bb['width'], bb['height']))
                 if self.show_overlay:
@@ -124,6 +173,9 @@ def classify_callback(self):
 
         # publish message
         self.image_publisher.publish(self.cv_bridge.cv2_to_imgmsg(cropped,"bgr8"))
+        self.results_publisher.publish(results_msg)
+        self.info_msg.header.stamp = time_now
+        self.info_publisher.publish(self.info_msg)
 
         self.occupied= False
         self.timer_classify.cancel()
@@ -166,6 +218,8 @@ def classify(self, img):
                 self.logger.error('Error on classification')
 
 
+
+
 def main():
     rclpy.init()
     node = EI_Image_node()
@@ -174,7 +228,6 @@ def main():
     node.destroy_node()
     rclpy.shutdown()
 
-
 if __name__ == "__main__":
    main()
 

package.xml

@@ -14,7 +14,7 @@
   <test_depend>ament_pep257</test_depend>
   <test_depend>python3-pytest</test_depend>
 
-  <!--<exec_depend>vision_msgs</exec_depend>-->
+  <exec_depend>vision_msgs</exec_depend>
   <exec_depend>sensor_msgs</exec_depend>
   <exec_depend>ros2launch</exec_depend>
 

setup.py

@@ -4,7 +4,7 @@
 submodules = 'edgeimpulse_ros/submodules'
 setup(
     name=package_name,
-    version='0.0.1',
+    version='0.0.2',
     packages=[package_name, submodules],
     data_files=[
         ('share/ament_index/resource_index/packages',