def predict(token):
try:
vprint("Processes: ", app.processes)
vprint("Predictors: ", app.predictors)
IMG_SIZE = 256
frame_proportion = 0.9
frame_offset_x = 0
frame_offset_y = 0
img = request.files['image']
if img is not None:
img_g = img.read()
img_np = np.fromstring(img_g, np.uint8)
frame = cv2.imdecode(img_np, cv2.IMREAD_COLOR)
if token in app.processes:
predictor = app.processes[token]['predictor']
frame = frame[..., ::-1]
frame_orig = frame.copy()
frame, lrudwh = crop(frame,
p=frame_proportion,
offset_x=frame_offset_x,
offset_y=frame_offset_y)
frame_lrudwh = lrudwh
frame = resize(frame, (IMG_SIZE, IMG_SIZE))[..., :3]
out = predictor.predict(frame)
if out is not None:
out = cv2.cvtColor(out, cv2.COLOR_BGR2RGB)
_, out = cv2.imencode('.jpg', out)
out = out.tobytes()
out = base64.b64encode(out).decode("utf-8")
return predict_response(
status=afy_flask_predict_status.SUCCESS, image=out)
return predict_response(
status=afy_flask_predict_status.SUCCESS)
return predict_response(
status=afy_flask_predict_status.NO_PREDICTOR,
error="Predictor not available")
return predict_response(
status=afy_flask_predict_status.INPUT_IMAGE_ERROR,
error="Invalid image / image corrupted")
except Exception as e:
if app.verbose:
traceback.print_exc()
return predict_response(error=str(e))
timing = {'preproc': 0, 'predict': 0, 'postproc': 0}
green_overlay = False
tt.tic()
ret, frame = cap.read()
if not ret:
log("Can't receive frame (stream end?). Exiting ...")
break
frame = frame[..., ::-1]
frame_orig = frame.copy()
frame, lrudwh = crop(frame,
p=frame_proportion,
offset_x=frame_offset_x,
offset_y=frame_offset_y)
frame_lrudwh = lrudwh
frame = resize(frame, (IMG_SIZE, IMG_SIZE))[..., :3]
if find_keyframe:
if is_new_frame_better(avatar, frame, predictor):
log("Taking new frame!")
green_overlay = True
predictor.reset_frames()
timing['preproc'] = tt.toc()
if passthrough:
out = frame
elif is_calibrated:
# FPS 值為 25.0，解析度為 512x512
inference_output = cv2.VideoWriter('video_output.mp4', fourcc, 15.0, (width, height))
record_flag = False
avatar = None
change_avatar(predictor, avatars[cur_ava])
cap = cv2.VideoCapture(r"C:\Users\taros\avatarify-python\input.mp4")
while(cap.isOpened()):
ret, frame = cap.read()
if ret:
log("reading frame")
frame = frame[..., ::-1]
frame_orig = frame.copy()
frame, (frame_offset_x, frame_offset_y) = crop(frame, p=frame_proportion, offset_x=frame_offset_x, offset_y=frame_offset_y)
frame = resize(frame, (IMG_SIZE, IMG_SIZE))[..., :3]
out = predictor.predict(frame)
if out is not None:
if not opt.no_pad:
out = pad_img(out, stream_img_size)
output_frame = cv2.resize(out[..., ::-1], (width, height))
# 寫入影格
inference_output.write(output_frame)
else:
log("stopping process")
inference_output.release()
cv2.destroyAllWindows()
