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()