From 238f159cab543a5d858945c96bd0a8b72f316b06 Mon Sep 17 00:00:00 2001 From: ashok Date: Wed, 2 Apr 2025 08:32:58 -0400 Subject: [PATCH] changed box size --- object_detection/yolo5blacks.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/object_detection/yolo5blacks.py b/object_detection/yolo5blacks.py index 64f07ad..943f431 100755 --- a/object_detection/yolo5blacks.py +++ b/object_detection/yolo5blacks.py @@ -43,7 +43,7 @@ def generate_frames(): """Capture video frames, apply object detection, and stream as MJPEG.""" stream_url = get_stream_url() if not stream_url: - print("❌ Failed to fetch stream URL!") + print(" Failed to fetch stream URL!") return print("🎥 Starting FFmpeg stream...") @@ -57,7 +57,7 @@ def generate_frames(): while True: raw_frame = ffmpeg_process.stdout.read(frame_width * frame_height * 3) # Read raw BGR frame if not raw_frame: - print("❌ No frame received!") + print("No frame received!") break frame = np.frombuffer(raw_frame, np.uint8).reshape((frame_height, frame_width, 3)) # Convert to NumPy array @@ -67,12 +67,12 @@ def generate_frames(): detections = results.pandas().xyxy[0] # Convert detections to Pandas DataFrame if detections.empty: - print("🚫 No objects detected in this frame.") + print("No objects detected in this frame.") frame = frame.copy() # Make a writable copy frame[:] = 0 # Make entire frame black else: - print(f"✅ Detected {len(detections)} objects!") + print(f"Detected {len(detections)} objects!") print(detections[["name", "confidence"]]) # Print detected object names and confidence mask = np.zeros_like(frame) # Create black mask @@ -81,9 +81,9 @@ def generate_frames(): if row["confidence"] > CONFIDENCE_THRESHOLD and row["name"].lower() in OBJECT_LIST: x1, y1, x2, y2 = int(row["xmin"]), int(row["ymin"]), int(row["xmax"]), int(row["ymax"]) - # Expand bounding box by 50px - x1, y1 = max(0, x1 - 50), max(0, y1 - 50) - x2, y2 = min(frame_width, x2 + 50), min(frame_height, y2 + 50) + # Expand bounding box by 75px + x1, y1 = max(0, x1 - 75), max(0, y1 - 75) + x2, y2 = min(frame_width, x2 + 75), min(frame_height, y2 + 75) # Copy detected object to mask mask[y1:y2, x1:x2] = frame[y1:y2, x1:x2] @@ -106,6 +106,6 @@ def video_feed(): return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame') if __name__ == '__main__': - print("🚀 Server running at http://localhost:5000/video") + print("Running at http://localhost:5000/video") #port app.run(host='0.0.0.0', port=5000, debug=True, threaded=True)