I've seen a number of issues raised about the predictions not being correct. When predicting on a face that's included in the VGG2 dataset I get all incorrect predictions. I've included a screen shot of the predictions. I am using the version 2 processing. The only change I made to the code was to replace keras with tensorflow.keras. However, I tested using base keras as well and I am not seeing correct predictions either.
tf.keras.backend.image_data_format()
model = VGGFace(model='resnet50', weights='vggface')
def predictFacePic(imagePath):
img = image.load_img(imagePath, target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = utils.preprocess_input(x, version=2)
preds = loaded_model.predict(x)
return utils.decode_predictions(preds)
I've seen a number of issues raised about the predictions not being correct. When predicting on a face that's included in the VGG2 dataset I get all incorrect predictions. I've included a screen shot of the predictions. I am using the version 2 processing. The only change I made to the code was to replace keras with tensorflow.keras. However, I tested using base keras as well and I am not seeing correct predictions either.