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@ -94,22 +94,8 @@ class TextRecognizer(object):
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def resize_norm_img(self, img, max_wh_ratio):
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def resize_norm_img(self, img, max_wh_ratio):
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imgC, imgH, imgW = self.rec_image_shape
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imgC, imgH, imgW = self.rec_image_shape
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if imgC == 1:
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if self.rec_algorithm == 'NRTR':
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img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# h = img.shape[0]
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# w = img.shape[1]
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# ratio = w / float(h)
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# if math.ceil(imgH * ratio) > imgW:
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# resized_w = imgW
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# else:
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# resized_w = int(math.ceil(imgH * ratio))
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# resized_image = cv2.resize(img, (resized_w, imgH))
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# #norm_img = np.expand_dims(resized_image, -1)
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# #norm_img = norm_img.transpose((2, 0, 1))
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# resized_image = resized_image.astype(np.float32) / 128. - 1.
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# padding_im = np.zeros((imgC, imgH, imgW), dtype=np.float32)
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# padding_im[0, :, 0:resized_w] = resized_image
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# return padding_im
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# return padding_im
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image_pil = Image.fromarray(np.uint8(img))
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image_pil = Image.fromarray(np.uint8(img))
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img = image_pil.resize([100, 32], Image.ANTIALIAS)
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img = image_pil.resize([100, 32], Image.ANTIALIAS)
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