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性别识别大部分都是识别到女生 在原本的代码下运行会报错,参照表型识别将代码更改为:
for (x, y, w, h) in faces: gray_face = gray[(y):(y + h), (x):(x + w)] gray_face = cv2.resize(gray_face, (64, 64)) gray_face = gray_face / 255.0 gray_face = np.expand_dims(gray_face, 0) gray_face = np.expand_dims(gray_face, -1) gender_label_arg = np.argmax(gender_classifier.predict(gray_face)) gender = gender_labels[gender_label_arg] cv2.rectangle(img, (x, y), (x + h, y + w), color, 2) img = chineseText.cv2ImgAddText(img, gender, x + h, y, color, 30)
目前不太清楚性别识别大部分识别为女性是否跟代码更改有关联,望指教
The text was updated successfully, but these errors were encountered:
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性别识别大部分都是识别到女生
在原本的代码下运行会报错,参照表型识别将代码更改为:
目前不太清楚性别识别大部分识别为女性是否跟代码更改有关联,望指教
The text was updated successfully, but these errors were encountered: