ValueError at / image / Tensor张量（“activation_5 / Softmax：0”，shape =（？，4），dtype = float32）不是该图的元素
您好我正在build立一个image processing的分类器，这个代码是一个API预测整个代码正在运行的图像的图像类除了这一行（pred = model.predict_classes（test_image））这个api是在Django框架和m使用python2.7
here is a point if I am running this code like normally ( without making an api)its running perfectly def classify_image(request): if request.method == 'POST' and request.FILES['test_image']: fs = FileSystemStorage() fs.save(request.FILES['test_image'].name, request.FILES['test_image']) test_image = cv2.imread('media/'+request.FILES['test_image'].name) if test_image is not None: test_image = cv2.resize(test_image, (128, 128)) test_image = np.array(test_image) test_image = test_image.astype('float32') test_image /= 255 print(test_image.shape) else: print('image didnt load') test_image = np.expand_dims(test_image, axis=0) print(test_image) print(test_image.shape) pred = model.predict_classes(test_image) print(pred) return JsonResponse(pred, safe=False) 您的test_image和tensorflow模型的input不匹配。
# Your image shape is (, , 3) test_image = cv2.imread('media/'+request.FILES['test_image'].name) if test_image is not None: test_image = cv2.resize(test_image, (128, 128)) test_image = np.array(test_image) test_image = test_image.astype('float32') test_image /= 255 print(test_image.shape) else: print('image didnt load') # Your image shape is (, , 4) test_image = np.expand_dims(test_image, axis=0) print(test_image) print(test_image.shape) pred = model.predict_classes(test_image)
以上只是假设。 如果你想debugging，我想你应该打印你的图像大小，并与您的模型定义的第一个布局进行比较。 并检查大小（宽度，高度，深度）是否匹配
