def main():
# initialization
bot_img = cv2.imread('squirrel.jpg') / 255.0
for i in range(256):
for j in range(256):
for k in range(3):
bottom_image[i, j, k] = bot_img[i, j, k]
target_img = cv2.imread('iclr2020.png')[:, :, 0] / 255.0
target_img = cv2.resize(target_img, (n_grid, n_grid))
target_img -= target_img.mean()
cv2.imshow('target', target_img * amplify + 0.5)
# print(target_img.min(), target_img.max())
for i in range(n_grid):
for j in range(n_grid):
target[i, j] = float(target_img[i, j])
initial[n_grid // 2, n_grid // 2] = 1
# forward('water_renderer/initial')
initial[n_grid // 2, n_grid // 2] = 0
from adversarial import vgg_grad, predict
for opt in range(10):
with ti.Tape(loss):
forward()
feed_to_vgg = np.zeros((224, 224, 3), dtype=np.float32)
# Note: do a transpose here
for i in range(224):
for j in range(224):
for k in range(3):
feed_to_vgg[i, j, k] = refracted_image[i + 16, j + 16,
2 - k]
predict(feed_to_vgg)
grad = vgg_grad(feed_to_vgg)
for i in range(224):
for j in range(224):
for k in range(3):
refracted_image.grad[i + 16, j + 16,
k] = grad[i, j, 2 - k] * 0.001
print('Iter', opt, ' Loss =', loss[None])
apply_grad()
forward('water_renderer/optimized')
def main():
allocate_fields()
# initialization
bot_img = cv2.imread('squirrel.jpg') / 255.0
for i in range(256):
for j in range(256):
for k in range(3):
bottom_image[i, j, k] = bot_img[i, j, k]
initial[n_grid // 2, n_grid // 2] = 1
# forward('water_renderer/initial')
initial[n_grid // 2, n_grid // 2] = 0
from adversarial import vgg_grad, predict
for opt in range(10):
with ti.Tape(loss):
forward()
feed_to_vgg = np.zeros((224, 224, 3), dtype=np.float32)
# Note: do a transpose here
for i in range(224):
for j in range(224):
for k in range(3):
feed_to_vgg[i, j, k] = refracted_image[i + 16, j + 16,
2 - k]
predict(feed_to_vgg)
grad = vgg_grad(feed_to_vgg)
for i in range(224):
for j in range(224):
for k in range(3):
refracted_image.grad[i + 16, j + 16,
k] = grad[i, j, 2 - k] * 0.001
print('Iter', opt)
apply_grad()
forward('water_renderer/optimized')