Grad_CAM_1.py

from vis.visualization import visualize_cam
from vis.utils import utils
from keras import activations

# Utility to search for layer index by name. 
# Alternatively we can specify this as -1 since it corresponds to the last layer.
layer_idx = utils.find_layer_idx(model, 'predictions')
#read the image and plot it
image = io.imread('car.jpeg')
io.imshow(image)

Grad_CAM_2.py

# Swap softmax with linear
model.layers[layer_idx].activation = activations.linear
model = utils.apply_modifications(model)

grads = visualize_cam(model, layer_idx,filter_indices=644,seed_input=image,backprop_modifier='guided')
# Plot with 'jet' colormap to visualize as a heatmap.
#grads = grads/grads.max()
plt.imshow(grads, cmap='jet')