def user_test_cam_sync_yolo(dev_idx, _user_id, test_loop): """User test cam yolo.""" image_source_w = 640 image_source_h = 480 image_size = image_source_w * image_source_h * 2 frames = [] # Setup video capture device. capture = kdp_wrapper.setup_capture(0, image_source_w, image_source_h) if capture is None: return -1 # Start ISI mode. if kdp_wrapper.start_isi(dev_idx, ISI_YOLO_ID, image_source_w, image_source_h): return -1 # Fill up the image buffers. img_id_tx = 0 start_time = time.time() while (img_id_tx != test_loop): kdp_wrapper.sync_inference(dev_idx, ISI_YOLO_ID, image_size, capture, img_id_tx, frames, handle_result) img_id_tx += 1 end_time = time.time() diff = end_time - start_time estimate_runtime = float(diff / test_loop) fps = float(1 / estimate_runtime) print("Sync inference average estimate runtime is ", estimate_runtime) print("Average FPS is ", fps) return 0
def user_test_cam_ssd_fd(dev_idx, _user_id, test_loop): """User test cam yolo.""" image_source_h = 480 image_source_w = 640 app_id = constants.APP_FD_LM image_size = image_source_w * image_source_h * 2 frames = [] # Setup video capture device. capture = kdp_wrapper.setup_capture(0, image_source_w, image_source_h) if capture is None: return -1 # Start ISI mode. if kdp_wrapper.start_isi(dev_idx, app_id, image_source_w, image_source_h): return -1 # Fill up the image buffers. ret, img_id_tx, img_left, buffer_depth = kdp_wrapper.fill_buffer( dev_idx, capture, image_size, frames) if ret: return -1 # Send the rest and get result in loop, with 2 images alternatively print("Companion image buffer depth = ", buffer_depth) return kdp_wrapper.pipeline_inference(dev_idx, app_id, test_loop, image_size, capture, img_id_tx, img_left, buffer_depth, frames, handle_result)
def detect_image(dev_idx, user_id): # Initialize image capture parameters frames = [] img_id_tx = 0 # Setup image path data_path = os.path.join(os.getcwd(), 'images') # Read input image image_name = input('Input image file: ') image_path = os.path.join(data_path, image_name) image_flag = os.path.isfile(image_path) # Start ISI mode if (kdp_wrapper.start_isi(dev_idx, ISI_YOLO_ID, IMG_SRC_WIDTH, IMG_SRC_HEIGHT)): return -1 # Perform image inference while image_flag: image = cv2.imread(image_path) kdp_examples.image_inference(dev_idx, ISI_YOLO_ID, image_size, image, img_id_tx, frames) img_id_tx += 1 image_name = input('Input image file: ') image_path = os.path.join(data_path, image_name) image_flag = os.path.isfile(image_path) cv2.destroyAllWindows()
def user_test_cam_yolo(dev_idx, _user_id, test_loop): """User test cam yolo.""" image_source_h = 480 image_source_w = 640 app_id = constants.APP_TINY_YOLO3 image_size = image_source_w * image_source_h * 2 frames = [] # Setup video capture device. capture = kdp_wrapper.setup_capture(0, image_source_w, image_source_h) if capture is None: return -1 # Start ISI mode. if kdp_wrapper.start_isi(dev_idx, app_id, image_source_w, image_source_h): return -1 start_time = time.time() # Fill up the image buffers. ret, img_id_tx, img_left, buffer_depth = kdp_wrapper.fill_buffer( dev_idx, capture, image_size, frames) if ret: return -1 # Send the rest and get result in loop, with 2 images alternatively print("Companion image buffer depth = ", buffer_depth) kdp_wrapper.pipeline_inference(dev_idx, app_id, test_loop - buffer_depth, image_size, capture, img_id_tx, img_left, buffer_depth, frames, handle_result) end_time = time.time() diff = end_time - start_time estimate_runtime = float(diff / test_loop) fps = float(1 / estimate_runtime) print("Pipeline inference average estimate runtime is ", estimate_runtime) print("Average FPS is ", fps) return 0
def detect_camera(dev_idx, user_id): # Initialize camera capture parameters frames = [] img_id_tx = 0 # Setup webcam capture capture = kdp_wrapper.setup_capture(0, IMG_SRC_WIDTH, IMG_SRC_HEIGHT) if capture is None: print("Can't open webcam") return -1 # Start ISI mode if (kdp_wrapper.start_isi(dev_idx, ISI_YOLO_ID, IMG_SRC_WIDTH, IMG_SRC_HEIGHT)): return -1 # Perform video inference while True: kdp_examples.camera_inference(dev_idx, ISI_YOLO_ID, image_size, capture, img_id_tx, frames) img_id_tx += 1 capture.release() cv2.destroyAllWindows()
print("Start kdp host lib ....\n") if (kdp_lib_start() < 0): print("Start kdp host lib failure") print("Start kdp task: ", args.task_name) # Setup video capture device. capture = kdp_wrapper.setup_capture(0, image_source_w, image_source_h) if capture is None: exit() if (args.task_name == "serial"): # Start ISI mode. if kdp_wrapper.start_isi(dev_idx, app_id, image_source_w, image_source_h): exit() img_id_tx = 0 start_time = time.time() while (img_id_tx != loop_count): kdp_wrapper.sync_inference(dev_idx, app_id, image_size, capture, img_id_tx, frames, handle_result) img_id_tx += 1 elif (args.task_name == "pipeline"): # Start ISI mode. if kdp_wrapper.start_isi(dev_idx, app_id, image_source_w, image_source_h): exit()