提交 72ebbf2d 编写于 作者: L LDOUBLEV

sorted outputs when export model

上级 d539508e
......@@ -142,8 +142,8 @@ class TextDetector(object):
outputs.append(output)
outs_dict = {}
if self.det_algorithm == "EAST":
outs_dict['f_score'] = outputs[0]
outs_dict['f_geo'] = outputs[1]
outs_dict['f_geo'] = outputs[0]
outs_dict['f_score'] = outputs[1]
else:
outs_dict['maps'] = outputs[0]
dt_boxes_list = self.postprocess_op(outs_dict, [ratio_list])
......@@ -169,14 +169,7 @@ if __name__ == "__main__":
total_time += elapse
count += 1
print("Predict time of %s:" % image_file, elapse)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
draw_img = draw_ocr(img, dt_boxes, None, None, False)
draw_img_save = "./inference_results/"
if not os.path.exists(draw_img_save):
os.makedirs(draw_img_save)
cv2.imwrite(
os.path.join(draw_img_save, os.path.basename(image_file)),
draw_img[:, :, ::-1])
print("The visualized image saved in {}".format(
os.path.join(draw_img_save, os.path.basename(image_file))))
"""
add visualized code
"""
print("Avg Time:", total_time / (count - 1))
......@@ -114,7 +114,6 @@ if __name__ == "__main__":
valid_image_file_list.append(image_file)
img_list.append(img)
rec_res, predict_time = text_recognizer(img_list)
rec_res, predict_time = text_recognizer(img_list)
for ino in range(len(img_list)):
print("Predicts of %s:%s" % (valid_image_file_list[ino], rec_res[ino]))
print("Total predict time for %d images:%.3f" %
......
......@@ -191,8 +191,8 @@ def build_export(config, main_prog, startup_prog):
func_infor = config['Architecture']['function']
model = create_module(func_infor)(params=config)
image, outputs = model(mode='export')
fetches_var = [outputs[name] for name in outputs]
fetches_var_name = [name for name in outputs]
fetches_var = sorted([outputs[name] for name in outputs])
fetches_var_name = [name for name in fetches_var]
feeded_var_names = [image.name]
target_vars = fetches_var
return feeded_var_names, target_vars, fetches_var_name
......
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