def viewFlow(flow_array, dimx, dimy, to_8bit = False, filename = None, show = True):
root = "..//data//output//testing_images"
if to_8bit:
flow_array = (flow_array * 255).astype(np.uint8)
colormap = img2rgb(flow_array, dimx, dimy)
im = Image.fromarray(colormap)
if show:
fig, ax = plt.subplots(1)
ax.imshow(im)
if filename is not None:
im.save(os.path.join(root,filename), quality=100)
def viewFlow(flow_array, dimx, dimy):
colormap = img2rgb(flow_array, dimx, dimy)
im = Image.fromarray(colormap)
fig, ax = plt.subplots(1)
ax.imshow(im)
from Vector_Extractor import exr2flow, img2rgb
data_path = "F://Flying_monkeys_2_RGB//test"
file_names = sorted(os.listdir(data_path))
i = 0
visual = False
for file in file_names:
if file.startswith("gt"):
i = i + 1
#img = np.load(os.path.join(data_path, file))
flow = np.load(os.path.join(data_path, file))
flow = np.reshape(flow, (192, 256, 2))
#print(np.shape(flow))
print(np.shape(flow))
if visual:
truth_colormap = img2rgb(flow, 256, 192)
im = Image.fromarray(truth_colormap)
fig, ax = plt.subplots(1)
ax.imshow(im)
np.save(os.path.join(data_path, file), flow)
#if i > 10:
# break
print(i)
#print(I[75:76])
lost_photons = sump - np.sum(example[:, :, 0])
file_name_flow = Flow_base + str(32).zfill(2) + '.exr'
# print(file_name)
image_set = exr2flow(os.path.join(data_path,file_name_flow ), 240, 200)
truth = image_set[0]
example_set = (example, truth)
if image_gen:
truth_colormap = img2rgb(example_set[1] ,240, 200)
im = Image.fromarray(truth_colormap)
fig, ax = plt.subplots(1)
ax.imshow(im)
ex_file_name = 'ex_' + str(i)
np.save(os.path.join(dataset_path, ex_file_name ), example_set)
#print(sump)
#print(lost_photons)
#print()
photons_list.append(sump)
lost_photons_list.append(lost_photons)
print("median of lost photons", statistics.median(lost_photons_list))
print("median of photons", statistics.median(photons_list))
if visualsave:
points_Image[:, :, 0] = example[:, :, 1]
points_Image[:, :, 1] = example[:, :, 3]
points_Image[:, :, 2] = example[:, :, 5]
pointsIMG = Image.fromarray(np.uint8(points_Image[:, :, 0] * 255 * 2))
pointsIMG.save(os.path.join(info_path, str(ex) + 'R.png'))
pointsIMG = Image.fromarray(np.uint8(points_Image[:, :, 1] * 255 * 2))
pointsIMG.save(os.path.join(info_path, str(ex) + 'G.png'))
pointsIMG = Image.fromarray(np.uint8(points_Image[:, :, 2] * 255 * 2))
pointsIMG.save(os.path.join(info_path, str(ex) + 'B.png'))
example_set = (example, truth)
if image_gen:
truth_colormap = img2rgb(example_set[1], 192, 256)
im = Image.fromarray(truth_colormap)
fig, ax = plt.subplots(1)
ax.imshow(im)
#ex_file_name = 'ex_' + str(i)
#np.save(os.path.join(dataset_path, ex_file_name ), example_set)
#print(sump)
#print(lost_photons)
#print()
photons_list.append(sump)
lost_photons_list.append(lost_photons)
if ex < number_train:
traindata_filename = "data_" + str(tr)
traingt_filename = "gt_" + str(tr)