Create server.py

Backend/server.py

+import queue
+import cv2
+import numpy as np
+import os
+from flask import Flask, Response, jsonify
+import time
+import threading
+
+
+app = Flask(__name__)
+
+
+#cap = cv2.VideoCapture(0)
+cap  = cv2.VideoCapture('sample_vids/chair_right.mp4')
+frame_queue = queue.Queue()
+
+# Load MobileNet SSD model
+net = cv2.dnn.readNetFromCaffe('MobileNetSSD_deploy.prototxt', 'MobileNetSSD_deploy.caffemodel')
+CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor", "laptop"]
+
+
+latest_direction = "No guidance available"
+latest_frame = None  
+frame_lock = threading.Lock()
+
+def continuous_detection():
+    global latest_direction, latest_frame
+    while True:
+        frame = frame_queue.get()
+        if frame is None:
+            break
+
+        start_time = time.time()  # Start time for FPS calculation
+        direction, processed_frame = detect_and_navigate(frame)
+        end_time = time.time()  # End time for FPS calculation
+
+        fps = 1 / (end_time - start_time)  # Calculate FPS
+        cv2.putText(processed_frame, f"FPS: {fps:.2f}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
+
+        with frame_lock:
+            latest_direction = direction
+            latest_frame = processed_frame
+
+
+# Start the continuous detection thread
+# detection_thread = threading.Thread(target=continuous_detection)
+# detection_thread.start()
+
+
+def detect_and_navigate(frame):
+    (h, w) = frame.shape[:2]
+    blob = cv2.dnn.blobFromImage(cv2.resize(frame, (300, 300)), 0.007843, (300, 300), 127.5)
+    net.setInput(blob)
+    detections = net.forward()
+
+    for i in range(detections.shape[2]):
+        confidence = detections[0, 0, i, 2]
+        if confidence > 0.5:
+            idx = int(detections[0, 0, i, 1])
+            if CLASSES[idx] in ["chair", "laptop","tvmonitor"]:
+                box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
+                (startX, startY, endX, endY) = box.astype("int")
+                label = "{}: {:.2f}%".format(CLASSES[idx], confidence * 100)
+                cv2.rectangle(frame, (startX, startY), (endX, endY), (0, 255, 0), 2)
+                y = startY - 15 if startY - 15 > 15 else startY + 15
+                cv2.putText(frame, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
+                # Determine direction
+                center_x = (startX + endX) // 2
+                if center_x < w // 3:
+                    direction = "Turn slightly left"
+                elif center_x > 2 * w // 3:
+                    direction = "Turn slightly right"
+                else:
+                    direction = "Go straight"
+                
+                print(direction)
+                return direction, frame
+
+    return "No guidance available", frame
+
+def display_output():
+    while True:
+        ret, frame = cap.read()
+        
+        # Check if the video has ended
+        if not ret:
+            cap.set(cv2.CAP_PROP_POS_FRAMES, 0)  # Reset video to the beginning
+            continue  # Skip the rest of the loop and start from the beginning
+
+        frame_queue.put(frame)
+
+        if latest_frame is not None:
+            cv2.imshow("Output", latest_frame)
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
+
+    cv2.destroyAllWindows()
+
+# @app.route('/video_feed')
+# def video_feed():
+#     def generate():
+#         while True:
+#             ret, frame = cap.read()
+#             if ret:
+#                 _, jpeg = cv2.imencode('.jpg', frame)
+#                 yield (b'--frame\r\n'
+#                        b'Content-Type: image/jpeg\r\n\r\n' + jpeg.tobytes() + b'\r\n\r\n')
+#     return Response(generate(), content_type='multipart/x-mixed-replace; boundary=frame')
+
+@app.route('/video_feed')
+def video_feed():
+    def generate():
+        global latest_frame
+        while True:
+            if frame_lock.acquire(False):  # Try to acquire the lock, but don't block
+                if latest_frame is not None:
+                    #_, jpeg = cv2.imencode('.jpg', latest_frame)
+
+
+                    compressed_frame = cv2.resize(latest_frame, (640, 480))  # Change to desired resolution
+                    
+                    # Compress the frame with reduced JPEG quality
+                    encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 45]  # Quality range is 0-100; lower means more compression
+                    _, jpeg = cv2.imencode('.jpg', compressed_frame, encode_param)
+                    
+                    frame_lock.release() 
+                    yield (b'--frame\r\n'
+                           b'Content-Type: image/jpeg\r\n\r\n' + jpeg.tobytes() + b'\r\n\r\n')
+                else:
+                    frame_lock.release()
+            else:
+                time.sleep(0.05)  # If we couldn't get the lock, wait a bit before trying again
+    return Response(generate(), content_type='multipart/x-mixed-replace; boundary=frame')
+
+
+
+@app.route('/direction')
+def get_direction():
+    with frame_lock:
+        return jsonify({"direction": latest_direction})
+
+def start_flask_app():
+    # Start the Flask app
+    app.run(host='0.0.0.0', port=5005, threaded=True)
+
+# if __name__ == '__main__':
+#     # Start the continuous detection thread
+#     detection_thread = threading.Thread(target=continuous_detection)
+#     detection_thread.start()
+
+#     # Call the display function in the main thread
+#     display_output()
+
+#     # Start the Flask app
+#     app.run(host='0.0.0.0', port=5000, threaded=True)
+
+if __name__ == '__main__':
+    # Start the continuous detection thread
+    detection_thread = threading.Thread(target=continuous_detection)
+    detection_thread.start()
+
+    # Start the Flask app in a separate thread
+    flask_thread = threading.Thread(target=start_flask_app)
+    flask_thread.start()
+
+    # Call the display function in the main thread
+    display_output()
\ No newline at end of file