Merge pull request #16 from Ar-Ray-code/feature/v0.2.1

Feature/v0.2.1

.gitignore

@@ -6,3 +6,5 @@ YOLOX_outputs/
 *.onnx
 *.trt
 *.engine
+YOLOX/
+YOLOX_outputs/

README.md

@@ -14,7 +14,7 @@
 | CUDA            |           | ✅           |
 | CUDA (FP16)     |           | ✅           |
 | TensorRT (CUDA) |  ✅       |              |
-| OpenVINO        |  ✅       |              |
+| OpenVINO        |  ✅       | ✅           |
 
 ### Raspberry Pi4 🍓 + NCS2 + YOLOX-ROS
 
@@ -39,27 +39,29 @@ Check [GitHub Wiki](https://github.com/Ar-Ray-code/YOLOX-ROS/wiki/YOLOX-ROS---Ra
 
 Install the dependent packages based on all tutorials.
 
-### STEP 1 : YOLOX Installation
+### STEP 1 : Download from GitHub
 
-[YOLOX Installation (Python)](https://github.com/Megvii-BaseDetection/YOLOX#quick-start)
+```bash
+mkdir -p ~/ros2_ws/src
+cd ~/ros2_ws/src
+git clone https://github.com/Ar-Ray-code/yolox_ros.git --recursive
+```
+
+### STEP 2 : YOLOX Installation (yolox_rps_py)
 
 ```bash
-git clone https://github.com/Megvii-BaseDetection/YOLOX.git
-cd YOLOX
-pip3 install -v -e .
+bash YOLOX-ROS/yolox_ros_py/install_yolox_py.bash
 ```
 
-### STEP 2 : Install YOLOX-ROS
+### STEP 3 : Install YOLOX-ROS
 
 ```bash
 source /opt/ros/foxy/setup.bash
 sudo apt install ros-foxy-v4l2-camera
-git clone --recursive https://github.com/Ar-Ray-code/yolox_ros.git ~/ros2_ws/src/yolox_ros/
-cd ~/ros2_ws
 colcon build --symlink-install # weights files will be installed automatically.
 ```
 
-### (Step 2) Using CUDA
+### (Step 3) Using CUDA
 
 If you have NVIDIA Graphics, you can run YOLOX-ROS on GPU.
 
@@ -82,48 +84,9 @@ ros2 launch yolox_ros_py yolox_s_cpu.launch.py
 
 </details>
 
-<details>
-<summary>C++ (OpenVINO)</summary>
-
-- Docker Images is [Released](https://github.com/Ar-Ray-code/YOLOX-ROS/tree/main/yolox_ros_cpp).
-
-## Requirements
-
-- ROS2 Foxy
-- OpenCV 4
-- OpenVINO
-- [bbox_ex_msgs](https://github.com/Ar-Ray-code/bbox_ex_msgs)
-
-### Step1 :  Installation
-
-```bash
-source /opt/ros/foxy/setup.bash
-sudo apt install ros-foxy-v4l2-camera
+## C++
 
-source /opt/intel/openvino_2021/bin/setupvars.sh
-cd ~/ros2_ws/src
-git clone --recursive https://github.com/Ar-Ray-code/YOLOX-ROS.git
-# Download onnx file and Convert to IR format.
-./YOLOX-ROS/weights/openvino/install.bash yolox_nano
-```
-
-### Step2 : Demo
-
-Connect your web camera.
-
-```bash
-source /opt/ros/foxy/setup.bash
-source ~/ros2_ws/install/local_setup.bash
-ros2 launch yolox_ros_cpp yolox_openvino.launch.py
-```
-</details>
-
-<details>
-<summary>C++ (TensorRT)</summary>
-
-Docker Images is [Released](https://github.com/Ar-Ray-code/YOLOX-ROS/tree/main/yolox_ros_cpp).
-
-</details>
+Check [this URL](https://github.com/Ar-Ray-code/YOLOX-ROS/tree/main/yolox_ros_cpp).
 
 
 ## Topic

weights/openvino/download_openvino_s.bash

@@ -0,0 +1,13 @@
+SCRIPT_DIR=$(cd $(dirname $0); pwd)
+cd $SCRIPT_DIR
+YOLOX_S_OPENVINO_TAR="yolox_s_openvino.tar.gz"
+# $SCRIPT_DIR/../weights/openvino/yolox_s.xml is exists
+if [ -f "$SCRIPT_DIR/yolox_s.xml" ]; then
+    echo "yolox_s.xml is exists"
+    exit 0
+else
+    wget https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/$YOLOX_S_OPENVINO_TAR -O $SCRIPT_DIR/$YOLOX_S_OPENVINO_TAR
+    tar -xvf $SCRIPT_DIR/$YOLOX_S_OPENVINO_TAR -C $SCRIPT_DIR/
+    rm $YOLOX_S_OPENVINO_TAR
+fi
+echo "Done. Please run `colcon build` to install."

yolox_ros_py/install_yolox_py.bash

@@ -0,0 +1,11 @@
+SCRIPT_DIR=$(cd $(dirname $0); pwd)
+cd $SCRIPT_DIR
+if [ -e "$SCRIPT_DIR/YOLOX/" ]; then
+    echo "YOLOX is exists"
+    exit 0
+fi
+git clone https://github.com/Megvii-BaseDetection/YOLOX.git
+cd YOLOX
+pip3 install -v -e .
+mv setup.py _setup.py
+mv setup.cfg _setup.cfg

yolox_ros_py/launch/yolox_s.launch.py

@@ -19,7 +19,7 @@ def generate_launch_description():
         parameters=[
             {"image_size/width": 640},
             {"image_size/height": 480},
-            {"yolo_type" : 'yolox-s'},
+            {"yolox_exp_py" : yolox_ros_share_dir+'/yolox_s.py'},
             {"device" : 'gpu'},
             {"fp16" : True},
             {"fuse" : False},

yolox_ros_py/launch/yolox_s_cpu.launch.py

@@ -19,7 +19,7 @@ def generate_launch_description():
         parameters=[
             {"image_size/width": 640},
             {"image_size/height": 480},
-            {"yolo_type" : 'yolox-s'},
+            {"yolox_exp_py" : yolox_ros_share_dir+'/yolox_s.py'},
             {"device" : 'cpu'},
             {"fp16" : True},
             {"fuse" : False},

yolox_ros_py/launch/yolox_openvino.launch.py → yolox_ros_py/launch/yolox_s_openvino.launch.py

@@ -4,6 +4,9 @@
 from ament_index_python.packages import get_package_share_directory
 from launch.launch_description_sources import PythonLaunchDescriptionSource
 
+from urllib.request import urlretrieve
+import os
+
 def generate_launch_description():
     yolox_ros_share_dir = get_package_share_directory('yolox_ros_py')
 
@@ -31,5 +34,5 @@ def generate_launch_description():
     return launch.LaunchDescription([
         webcam,
         yolox_openvino,
-        rqt_graph
+        # rqt_graph
     ])

yolox_ros_py/setup.py

@@ -15,7 +15,9 @@
 YOLOX_NANO_WEIGHTS = 'yolox_nano.pth'
 YOLOX_TINY_WEIGHTS = 'yolox_tiny.pth'
 
-BASE_LINK = 'https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/'
+YOLOX_VERSION = '0.1.1rc0'
+
+BASE_LINK = 'https://github.com/Megvii-BaseDetection/YOLOX/releases/download/'+YOLOX_VERSION+'/'
 YOLOX_S_WEIGHTS_URL = BASE_LINK + YOLOX_S_WEIGHTS
 YOLOX_M_WEIGHTS_URL = BASE_LINK + YOLOX_M_WEIGHTS
 YOLOX_L_WEIGHTS_URL = BASE_LINK + YOLOX_L_WEIGHTS
@@ -38,21 +40,7 @@
 if not os.path.exists(YOLOX_S_WEIGHTS_PATH):
     urlretrieve(YOLOX_S_WEIGHTS_URL, YOLOX_S_WEIGHTS_PATH)
 
-# if not os.path.exists(YOLOX_M_WEIGHTS_PATH):
-#     urlretrieve(YOLOX_M_WEIGHTS_URL, YOLOX_M_WEIGHTS_PATH)
-
-# if not os.path.exists(YOLOX_L_WEIGHTS_PATH):
-#     urlretrieve(YOLOX_L_WEIGHTS_URL, YOLOX_L_WEIGHTS_PATH)
-
-# if not os.path.exists(YOLOX_X_WEIGHTS_PATH):
-#     urlretrieve(YOLOX_X_WEIGHTS_URL, YOLOX_X_WEIGHTS_PATH)
-
-# if not os.path.exists(YOLOX_DARKNET53_WEIGHTS_PATH):
-#     urlretrieve(YOLOX_DARKNET53_WEIGHTS_URL, YOLOX_DARKNET53_WEIGHTS_PATH)
-
-# if not os.path.exists(YOLOX_NANO_WEIGHTS_PATH):
-#     urlretrieve(YOLOX_NANO_WEIGHTS_URL, YOLOX_NANO_WEIGHTS_PATH)
-
+# Download examples
 # if not os.path.exists(YOLOX_TINY_WEIGHTS_PATH):
 #     urlretrieve(YOLOX_TINY_WEIGHTS_URL, YOLOX_TINY_WEIGHTS_PATH)
 
@@ -68,6 +56,7 @@
         (os.path.join('share', package_name), glob('./launch/*.launch.py')),
         (os.path.join('share', package_name), glob('../weights/*.pth')),
         (os.path.join('share', package_name), glob('../weights/openvino/*')),
+        (os.path.join('share', package_name), glob('./YOLOX/exps/default/*.py')),
     ],
     install_requires=['setuptools'],
     zip_safe=True,

yolox_ros_py/yolox_ros_py/yolox_openvino.py

@@ -7,8 +7,6 @@
 
 import argparse
 import logging as log
-import os
-import sys
 
 import cv2
 import numpy as np
@@ -126,7 +124,7 @@ def imageflow_callback(self,msg:Image) -> None:
             _, _, h, w = self.net.input_info[self.input_blob].input_data.shape
             mean = (0.485, 0.456, 0.406)
             std = (0.229, 0.224, 0.225)
-            image, ratio = preprocess(origin_img, (h, w), mean, std)
+            image, ratio = preprocess(origin_img, (h, w))#, mean, std)
 
             res = self.exec_net.infer(inputs={self.input_blob: image})
             res = res[self.out_blob]
@@ -136,17 +134,17 @@ def imageflow_callback(self,msg:Image) -> None:
 
             boxes = predictions[:, :4]
             scores = predictions[:, 4, None] * predictions[:, 5:]
-            print(scores)
+            # print(scores)
 
             boxes_xyxy = np.ones_like(boxes)
             boxes_xyxy[:, 0] = boxes[:, 0] - boxes[:, 2]/2.
             boxes_xyxy[:, 1] = boxes[:, 1] - boxes[:, 3]/2.
             boxes_xyxy[:, 2] = boxes[:, 0] + boxes[:, 2]/2.
             boxes_xyxy[:, 3] = boxes[:, 1] + boxes[:, 3]/2.
-            boxes_xyxy /= ratio
+            # boxes_xyxy /= ratio
             dets = multiclass_nms(boxes_xyxy, scores, nms_thr=0.45, score_thr=0.1)
 
-            print(dets)
+            # print(dets)
             if dets is not None:
                 final_boxes = dets[:, :4]
                 final_scores, final_cls_inds = dets[:, 4], dets[:, 5]
@@ -162,13 +160,13 @@ def imageflow_callback(self,msg:Image) -> None:
 
             try:
                 bboxes = self.yolox2bboxes_msgs(dets[:, :4], final_scores, final_cls_inds, COCO_CLASSES, msg.header)
-                self.get_logger().info(f'bboxes: {bboxes}')
+                # self.get_logger().info(f'bboxes: {bboxes}')
                 if (self.imshow_isshow):
                     cv2.imshow("YOLOX",origin_img)
                     cv2.waitKey(1)
 
             except:
-                self.get_logger().info('No object detected')
+                # self.get_logger().info('No object detected')
                 if (self.imshow_isshow):
                     cv2.imshow("YOLOX",origin_img)
                     cv2.waitKey(1)

yolox_ros_py/yolox_ros_py/yolox_ros.py

@@ -136,7 +136,9 @@ def setting_yolox_exp(self) -> None:
 
         self.declare_parameter('imshow_isshow',True)
 
-        self.declare_parameter('yolo_type','yolox-s')
+        # self.declare_parameter('yolo_type','yolox-s')
+        self.declare_parameter('yolox_exp_py', '')
+
         self.declare_parameter('fuse',False)
         self.declare_parameter('trt', False)
         self.declare_parameter('fp16', False)
@@ -152,11 +154,14 @@ def setting_yolox_exp(self) -> None:
         self.declare_parameter('resize', 640)
         self.declare_parameter('image_size/width', 640)
         self.declare_parameter('image_size/height', 480)
+
 
         # =============================================================
         self.imshow_isshow = self.get_parameter('imshow_isshow').value
 
-        yolo_type = self.get_parameter('yolo_type').value
+        # yolo_type = self.get_parameter('yolo_type').value
+        exp_py = self.get_parameter('yolox_exp_py').value
+
         fuse = self.get_parameter('fuse').value
         trt = self.get_parameter('trt').value
         fp16 = self.get_parameter('fp16').value
@@ -175,7 +180,9 @@ def setting_yolox_exp(self) -> None:
 
         cudnn.benchmark = True
 
-        exp = get_exp(None, yolo_type)
+        # exp = get_exp(None, "yolox-s")
+        exp = get_exp(exp_py, None)
+
 
         BASE_PATH = os.getcwd()
         file_name = os.path.join(BASE_PATH, "YOLOX_PATH/")