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- import os
- import cv2
- import numpy as np
- from click_captcha.model import mobile_net, cnn_net, u_net_drag
- from click_captcha.utils import pil_resize
- image_shape = (128, 256, 3)
- weights_path = "./models/drag_f1_0.42.h5"
- project_dir = os.path.dirname(os.path.abspath(__file__)) + "/../"
- def recognize(image_path):
- model = u_net_drag(input_shape=image_shape)
- model.load_weights(weights_path)
- img = cv2.imread(image_path)
- img = pil_resize(img, image_shape[0], image_shape[1])
- cv2.imshow("img", img)
- img = img / 255.
- X = np.expand_dims(img, 0)
- pred = model.predict(X)
- pred = pred[0][..., 0]
- pred = np.expand_dims(pred, axis=-1)
- pred = np.concatenate([pred]*3, axis=-1)
- pred = np.uint8(pred*255.)
- print(pred.shape)
- cv2.imshow("pred", pred)
- w = np.argmax(np.mean(np.mean(pred, axis=0), axis=-1))
- print(w)
- decode = np.zeros(pred.shape, np.uint8)
- decode[:, w, :] = 255
- cv2.imshow("decode", decode)
- cv2.waitKey(0)
- # index = int(np.argmax(pred))
- # with open(project_dir + "data/chinese_5710.txt") as f:
- # char_str = f.read()
- # char = char_str[index]
- # print("recognize chinese", char)
- return
- if __name__ == "__main__":
- _path = "../data/test/yolo_16.jpg"
- # _path = "../data/drag/3.jpg"
- recognize(_path)
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