camera_module has full featured face detect

build_cam.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+
+cd ~/ros2_ws
+source /opt/ros/kilted/setup.bash  # Use system ROS setup if needed
+
+rm -rf build/camera_module install/camera_module log
+
+# Build only camera_module
+colcon build --packages-select camera_module --event-handlers console_direct+
+
+# Source overlay
+source install/setup.bash
+camera_module camera_module

index.html

@@ -34,6 +34,13 @@
       background: #d0f0c0;
       transition: background 0.5s ease;
     }
+
+    #cameraImage {
+  display: block;
+  margin-top: 1em;
+  border: 1px solid #ccc;
+}
+
   </style>
 </head>
 
@@ -55,7 +62,8 @@
   </div>
   <p>Current publish rate: <span id="currentRate">1.0</span> Hz</p>
   <h2>Live Camera Feed</h2>
-  <img id="cameraImage" width="640" height="480" alt="Camera Feed">
+  <img id="cameraImage" style="max-width: 100%; height: auto;" alt="Camera Feed">
+
 
   <script>
     const ros = new ROSLIB.Ros({ url: 'ws://192.168.1.205:9090' });

src/camera_module/camera_module/camera_module.py

@@ -11,6 +11,7 @@ from cv_bridge import CvBridge
 import time
 from camera_module.threaded_node import ThreadedNode
 
+from sensor_msgs.msg import CompressedImage
 from std_msgs.msg import String
 import rclpy
 
@@ -25,9 +26,11 @@ model_path = os.path.join(get_package_share_directory(package_name), 'resource',
 class CamPublisher(ThreadedNode):
     def __init__(self, rknn, cap):
         super().__init__('camera_module', default_rate=5.0)
-        self.string_pub = self.create_publisher(String, 'camera_module/cam_topic', 10)
-        self.image_pub = self.create_publisher(CompressedImage, 'camera_module/compressed', 10)
+        #self.string_pub = self.create_publisher(String, 'camera_module/cam_topic', 10)
+        #self.image_pub = self.create_publisher(CompressedImage, 'camera_module/compressed', 10)
         self.face_detect_pub = self.create_publisher(String, 'camera_module/face_data', 10)
+        self.face_image_pub = self.create_publisher(CompressedImage, 'camera_module/face_images', 10)
+        self.face_detect_frame_pub = self.create_publisher(CompressedImage, 'camera_module/face_detect_frame', 10)
         self.rknn = rknn
         self.cap = cap
         self.latest_frame = None
@@ -63,6 +66,8 @@ class CamPublisher(ThreadedNode):
         ret, frame = cap.read()
         if not ret:
             return
+        raw_frame = frame.copy()
+
         img_height, img_width, _ = frame.shape
         letterbox_img, aspect_ratio, offset_x, offset_y = letterbox_resize(frame, self.model_size, 114)
         infer_img = np.expand_dims(letterbox_img.astype(np.uint8), axis=0)
@@ -95,6 +100,10 @@ class CamPublisher(ThreadedNode):
         face_data = []
         frame_center = np.array([img_width / 2, img_height / 2])
 
+        face_data = []
+        valid_dets = []
+        valid_landms = []
+
         for data, landmark in zip(dets, landms):
             if data[4] < 0.6:
                 continue
@@ -110,6 +119,13 @@ class CamPublisher(ThreadedNode):
                     "y": float(offset[1])
                 }
             })
+            valid_dets.append(data)
+            valid_landms.append(landmark)
+
+
+        for data, landmark in zip(valid_dets, valid_landms):
+            x1, y1, x2, y2 = map(int, data[:4])
+            conf = data[4]
             cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
             cv2.putText(frame, f'{conf:.4f}', (x1, y1 + 12), cv2.FONT_HERSHEY_DUPLEX, 0.5, (255, 255, 255))
             for j in range(5):
@@ -121,10 +137,41 @@ class CamPublisher(ThreadedNode):
         if len(face_data) > 0:
             print(face_data)
             self.face_detect_pub.publish(String(data=str(face_data)))
+
+        # CROP FACES AND PUBLISH STITCHED IMAGE
+        face_crops = []
+        for data in dets:
+            if data[4] < 0.6:
+                continue
+            x1, y1, x2, y2 = map(int, data[:4])
+            face_crop = raw_frame[y1:y2, x1:x2]
+            face_crops.append(face_crop)
+        target_height = 100
+        resized_faces = [
+            cv2.resize(face, (int(face.shape[1] * target_height / face.shape[0]), target_height))
+            for face in face_crops
+        ]
+        if resized_faces:
+            stitched = cv2.hconcat(resized_faces)
+            ret, stitched_buffer = cv2.imencode('.jpg', stitched)
+            if ret:
+                msg = CompressedImage()
+                msg.header.stamp = self.get_clock().now().to_msg()
+                msg.format = 'jpeg'
+                msg.data = stitched_buffer.tobytes()
+                self.face_image_pub.publish(msg)
+
+            
+            
         ret, buffer = cv2.imencode('.jpg', frame)
         if ret:
             latest_frame = buffer.tobytes()
             latest_faces = face_data
+            msg = CompressedImage()
+            msg.header.stamp = self.get_clock().now().to_msg()
+            msg.format = 'jpeg'
+            msg.data = buffer.tobytes()
+            self.face_detect_frame_pub.publish(msg)
 
     def destroy_node(self):
         if self.cap: