def user_test_single_dme(dev_idx, loop):
"""Test single dme."""
# load model into Kneron device
model_path = "../test_images/dme_yolo_224"
kdp_wrapper.kdp_dme_load_yolo_model(dev_idx, model_path)
image_source_h = 480
image_source_w = 640
image_size = image_source_w * image_source_h * 2
frames = []
app_id = constants.APP_TINY_YOLO3
# Setup video capture device.
capture = kdp_wrapper.setup_capture(0, image_source_w, image_source_h)
if capture is None:
return -1
# Send 1 image to the DME image buffers.
ret, ssid = kdp_wrapper.dme_fill_buffer(dev_idx, capture, image_size,
frames)
if ret:
return -1
kdp_wrapper.dme_pipeline_inference(dev_idx, app_id, loop, image_size,
capture, ssid, frames, handle_result)
kdp_wrapper.kdp_exit_dme(dev_idx)
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_single_dme(dev_idx, loop):
"""Test single dme."""
# load model into Kneron device
model_path = "../test_images/dme_ssd_fd"
is_raw_ouput = True
kdp_wrapper.kdp_dme_load_ssd_model(dev_idx, model_path, is_raw_ouput)
image_source_h = 480
image_source_w = 640
image_size = image_source_w * image_source_h * 2
frames = []
app_id = 0 # if app_id is 0, output raw data for kdp_wrapper.kdp_dme_inference
# the parameters for postprocess
anchor_path = './examples/fdssd/models/anchor_face.npy'
model_input_shape = (200, 200)
score_thres = 0.5
nms_thres = 0.35
only_max = False
# Setup video capture device.
capture = kdp_wrapper.setup_capture(0, image_source_w, image_source_h)
if capture is None:
return -1
while (loop):
raw_res = kdp_wrapper.kdp_dme_inference(dev_idx, app_id, capture, image_size, frames)
det_res = postprocess_(raw_res, anchor_path, model_input_shape,
image_source_w, image_source_h, score_thres, only_max, nms_thres)
draw_result(dev_idx, det_res, frames)
loop -= 1
kdp_wrapper.kdp_exit_dme(dev_idx)
def user_test_single_dme(dev_idx, loop):
"""Test single dme."""
# load model into Kneron device
model_path = "../test_images/dme_ssd_fd"
is_raw_ouput = False
kdp_wrapper.kdp_dme_load_ssd_model(dev_idx, model_path, False)
image_source_h = 480
image_source_w = 640
image_size = image_source_w * image_source_h * 2
frames = []
app_id = constants.APP_FD_LM
# Setup video capture device.
capture = kdp_wrapper.setup_capture(0, image_source_w, image_source_h)
if capture is None:
return -1
while (loop):
det_res = kdp_wrapper.kdp_dme_inference(dev_idx, app_id, capture, image_size, frames)
draw_result(dev_idx, det_res, frames)
loop -= 1
# print("Total class {}: total detection {}".format(det_res[0], det_res[1]))
# for i in range(det_res[1]):
# print("x1,y1,x2,y2:", det_res[4*i+2],det_res[4*i+3],det_res[4*i+4],det_res[4*i+5])
kdp_wrapper.kdp_exit_dme(dev_idx)
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 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_parallel(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("Parallel 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()
def user_test_single_dme(dev_idx, loop):
"""Test single dme."""
# load model into Kneron device
model_path = "../test_images/dme_yolo_224"
kdp_wrapper.kdp_dme_load_yolo_model(dev_idx, model_path)
image_source_h = 480
image_source_w = 640
image_size = image_source_w * image_source_h * 2
frames = []
app_id = constants.APP_TINY_YOLO3
# the parameters for postprocess
anchor_path = './examples/yolo/models/anchors.txt'
class_path = './common/coco_name_lists'
model_input_shape = (224, 224)
score_thres = 0.2
nms_thres = 0.45
keep_aspect_ratio = True
# Setup video capture device.
capture = kdp_wrapper.setup_capture(0, image_source_w, image_source_h)
if capture is None:
return -1
while (loop):
raw_res = kdp_wrapper.kdp_dme_inference(dev_idx, app_id, capture, image_size, frames)
dets = yolo_postprocess_(raw_res, anchor_path, class_path, image_source_h, image_source_w, model_input_shape,
score_thres, nms_thres, keep_aspect_ratio)
# print("dets: ", dets)
draw_result(dev_idx, dets, frames)
loop -= 1
kdp_wrapper.kdp_exit_dme(dev_idx)
if (kdp_lib_init() < 0):
print("Initialize kdp host lib failure\n")
print("Add kdp device ....")
dev_idx = kdp_add_dev(KDP_USB_DEV, "")
if (dev_idx < 0):
print("Add kdp device failure\n")
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