How to save frame?

Accelerated Computing Intelligent Video Analytics DeepStream SDK
1

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) nano
• DeepStream Version 7.0
• JetPack Version (valid for Jetson only) 6.0
• TensorRT Version8.6.2.3-1+cuda12.2
• NVIDIA GPU Driver Version (valid for GPU only) NVIDIA-SMI 540.2.0
• Issue Type( questions, new requirements, bugs)

How to save face ROI ? In below code it return n_frame = pyds.get_nvds_buf_surface(hash(gst_buffer), frame_meta.batch_id)
RuntimeError: get_nvds_buf_Surface: Currently we only support RGBA color Format

def tracker_src_pad_buffer_probe(pad, info, user_data):
buf = info.get_buffer()
batch_meta = pyds.gst_buffer_get_nvds_batch_meta(hash(buf))

gst_buffer = info.get_buffer()
if not gst_buffer:
    print("Unable to get GstBuffer ")
    return

# # Retrieve the caps of the pad to inspect the format
# caps = pad.get_current_caps()
# caps_structure = caps.get_structure(0)

# # Print the color format
# color_format = caps_structure.get_string("format")
# print(f"Buffer Color Format: {color_format}")

l_frame = batch_meta.frame_meta_list
while l_frame:
    try:
        frame_meta = pyds.NvDsFrameMeta.cast(l_frame.data)
    except StopIteration:
        break

    current_index = frame_meta.source_id

    l_obj = frame_meta.obj_meta_list
    while l_obj:
        try:
            obj_meta = pyds.NvDsObjectMeta.cast(l_obj.data)
        except StopIteration:
            break

        parse_face_from_meta(frame_meta, obj_meta)
        set_custom_bbox(obj_meta)

        n_frame = pyds.get_nvds_buf_surface(hash(gst_buffer), frame_meta.batch_id)

        # Get bounding box coordinates
        # rect_params = obj_meta.rect_params
        # top = max(int(rect_params.top), 0)
        # left = max(int(rect_params.left), 0)
        # width = max(int(rect_params.width), 0)
        # height = max(int(rect_params.height), 0)

        # Check if conditions are met for saving the frame
        # if saved_count["stream_{}".format(frame_meta.pad_index)] % 30 == 0 and (
        #         MIN_CONFIDENCE < obj_meta.confidence < MAX_CONFIDENCE):
        # if is_first_obj:
        #     is_first_obj = False
            # Getting Image data using nvbufsurface
            
        #n_frame = pyds.get_nvds_buf_surface(hash(gst_buffer), frame_meta.batch_id)
        # Annotate the frame with bounding boxes
        #n_frame = draw_bounding_boxes(n_frame, obj_meta, obj_meta.confidence)
        # Convert python array into numpy array format
        frame_copy = np.array(n_frame, copy=True, order='C')
        # Convert the array into cv2 default color format
        frame_copy = cv2.cvtColor(frame_copy, cv2.COLOR_RGBA2BGRA)
        
        # # If Jetson, unmap the buffer after processing
        # if platform_info.is_integrated_gpu():
        #     pyds.unmap_nvds_buf_surface(hash(gst_buffer), frame_meta.batch_id)

        save_image = True
    
        try:
            l_obj = l_obj.next
        except StopIteration:
            break
    
    img_path = "{}/stream_{}/frame_{}.jpg".format(folder_name, frame_meta.pad_index, frame_meta.frame_num)
    # Create directory if it doesn't exist
    os.makedirs(os.path.dirname(img_path), exist_ok=True)
    # Save the image
    #cv2.imwrite(img_path, frame_copy)
    print(f"Saved image to {img_path}")

    fps_streams['stream{0}'.format(current_index)].get_fps()

    try:
        l_frame = l_frame.next
    except StopIteration:
        break

return Gst.PadProbeReturn.OK
3

This is duplicated with the 300762.

4

Thank you very much Sir. Problem Solved . Its extracted frame successfully inside def osd_sink_pad_buffer_probe(pad, info, u_data): Your guidance truly helped solve the problem successfully.

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