from vgg16 import model

dirname = os.path.dirname(os.path.abspath(__file__))

layer_idx = 18

img_disp = cv2.imread('{}/images/woh.png'.format(dirname))

img_disp = cv2.resize(img_disp, (224, 224))

img = img_disp[np.newaxis, :, :, :]

img = img.astype(np.float32)

img = img - np.array([103.939, 116.779, 123.68]) # bgr

for i, layer in enumerate(model.layers):

print(i, layer)

compute_weight = True

is_changed = True

while True:

if is_changed:

is_changed = False

out = utils.activation(img, model, layer_idx)

if len(out.shape) == 4:

is_conv = True

is_fc = False

out = np.transpose(out, (3, 1, 2, 0))

else:

is_conv = False

is_fc = True

out = np.transpose(out, (1, 0))

out = utils.normalize(out)

disp = utils.combine_and_fit(out, is_conv=is_conv, is_fc=is_fc, disp_w=800)

cv2.imshow('input', img_disp)

cv2.imshow('disp', disp)

if compute_weight:

compute_weight = False

weight = model.get_weights()[0] # only first layer is interpretable for *me*

weight = utils.normalize_weights(weight, 'conv')

weight = np.transpose(weight, (3, 0, 1, 2))

weight_disp = utils.combine_and_fit(weight, is_weights=True, disp_w=400)

cv2.imshow('weight_disp', weight_disp)

val = cv2.waitKey(1) & 0xFF

if val == ord('q'):

break

elif val == ord('w'):

if layer_idx < 22:

layer_idx += 1

is_changed = True

print(model.layers[layer_idx].name)

elif val == ord('s'):

if layer_idx > 1:

layer_idx -= 1

is_changed = True