rcmalli/keras-vggface

Issue changing input_shape to (100,100,3)

jaimerodric opened this issue · 0 comments

My code is this one, and changing only the input_shape I get a error:
`

def fine_VGGFace():
    model = VGGFace(model="resnet50", include_top=False, input_shape=(100, 100, 3), pooling="avg", weights='vggface')
model.trainable = False

x = model.output

x = tf.keras.layers.Dense(1024, name='fc8', activation=None)(x)

output = tf.keras.layers.Lambda(lambda x: tf.math.l2_normalize(x, axis=1))(x)  # L2 normalize embeddings

model_finetuning2 = tf.keras.Model(inputs=model.inputs, outputs=[output])
model_finetuning2.summary()

return model_finetuning2`

Exception encountered when calling layer "avg_pool" (type AveragePooling2D).

Negative dimension size caused by subtracting 7 from 3 for '{{node avg_pool/AvgPool}} = AvgPoolT=DT_FLOAT, data_format="NHWC", ksize=[1, 7, 7, 1], padding="VALID", strides=[1, 7, 7, 1]' with input shapes: [?,3,3,2048].