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Yolo_tfserving_helper
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class YoloHelper: | |
def preprocess(self, image): | |
image = img_to_array(image, ) | |
data = cv2.resize(image, (416, 416)) | |
# im_arr = img_to_array(data, ) | |
im_arr = data/255.0 | |
im_arr = np.expand_dims(im_arr, axis=0) | |
return im_arr | |
def predict(self, image ,threshold =0.6): | |
channel = implementations.insecure_channel(current_config.TF_SERVING_HOSTNAME, | |
current_config.TENSORFLOW_SERVING_PORT) | |
stub = prediction_service_pb2.beta_create_PredictionService_stub(channel) | |
predict_request = predict_pb2.PredictRequest() | |
predict_request.model_spec.name = current_config.name | |
predict_request.model_spec.signature_name = current_config.signature_name | |
predict_request.inputs[current_config.input_name].CopyFrom( | |
tf.contrib.util.make_tensor_proto(image, dtype=tf.float32)) | |
try: | |
result = stub.Predict(predict_request, 10.0) # 10 secs timeout | |
except ExpirationError as e: | |
return {{'errors': [{'message': 'Deadline exceed or Connect Failed'}]}, \ | |
{'status_code': 400}} | |
else: | |
return self.post_process(result,threshold) | |
def post_process(self, image, threshold =0.6): | |
predictions = image.outputs[current_config.output_name] | |
predictions = tf.make_ndarray(predictions) | |
img_arr = np.squeeze(predictions, 0) | |
path = current_config.yolo_config | |
meta = parse_cfg(path=path) | |
meta.update(current_config.labels) | |
boxes = box_contructor(meta=meta, out=img_arr, threshold=threshold) | |
boxesInfo = list() | |
print(len(boxes)) | |
for box in boxes: | |
tmpBox, prob_ = process_box(b=box, h=13, w=13, threshold=threshold, meta=meta) | |
if tmpBox is None: | |
continue | |
boxesInfo.append({'od_output': tmpBox, 'od_score': round(float(prob_ * 100), 2)}) | |
if len(boxesInfo) > 0: | |
score_list = [] | |
index = [] | |
for i, score in enumerate(box['od_score'] for box in boxesInfo): | |
score_list.append(score) | |
index.append(i) | |
index = np.argmax(score_list) | |
name = boxesInfo[index]['od_output'] | |
response = {"Predicted ": name} | |
return response | |
return {"Predicted ": None} |
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