I'm running TF as backend ( I might as well because Theano is now dead
and i've been having trouble running the RESNET example from Lesson 7 (particularly multi-target classifier and transfer learning)
Has anyone been able to do run RESNET example either
1) on Jeremy's code (lesson 7 video), but with TF backend?
Problem here: calling
model = Resnet50(include_top=False)
gets this error , which I haven't been able to google:
ValueError: It seems that you are using the Keras 2 and you are passing both
strides as integer positional arguments. For safety reasons, this is disallowed. Pass
strides as a keyword argument instead.
Note, I am using using updated resnet50.py file from one of the students github that was made to include Keras2.0 changes
2) Resnet using Kera's built-in resnet from keras.applications module?
Problem incurred here:
from keras.models import Sequential
from keras.applications import ResNet50
from keras.applications import imagenet_utils
from keras.applications.inception_v3 import preprocess_input
from keras.utils import get_file
from keras.preprocessing.image import img_to_array, load_img
import numpy as np
from utils import *
model = ResNet50(weights="imagenet")
[ model.layers.pop() for _ in range(3) ] # i had to this to mimick Jeremy's resnet model
however, in Jeremy's model output_shape, it was (2048,7,7)
where as this models's output_shape is (1000,)
What's the discrepancy?