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)