diff options
Diffstat (limited to 'test.py')
| -rw-r--r-- | test.py | 51 |
1 files changed, 31 insertions, 20 deletions
@@ -6,7 +6,7 @@ from util.visualizer import Visualizer from util.util import mkdirs from util import html from shutil import move, copyfile -from PIL import Image, ImageOps +from PIL import Image, ImageOps, ImageFilter from skimage.transform import resize from scipy.misc import imresize from shutil import copyfile, rmtree @@ -24,11 +24,13 @@ if __name__ == '__main__': opt.experiment = opt.start_img.split("/")[-1].split(".")[0] render_dir = opt.results_dir + opt.name + "/exp:" + opt.experiment + "/" + mov_dir = "mov/" if os.path.exists(render_dir): - rmtree(render_dir) + rmtree(render_dir) mkdirs(render_dir) - copyfile(opt.start_img, render_dir + "frame_00000.png") + if opt.start_img != 'test.jpg': + copyfile(opt.start_img, render_dir + "frame_00000.png") data_loader = CreateRecursiveDataLoader(opt) dataset = data_loader.load_data() @@ -49,11 +51,11 @@ if __name__ == '__main__': img_path = model.get_image_paths() print('%04d: process image... %s' % (i, img_path)) ims = visualizer.save_images(webpage, visuals, img_path, aspect_ratio=opt.aspect_ratio) + im = visuals['fake_B'] + save_path = render_dir + "frame_{:05d}_tmp.png".format(i+1) + final_path = render_dir + "frame_{:05d}.png".format(i+1) if dataset.name() == 'RecursiveDatasetDataLoader': # print(visuals.keys()) - im = visuals['fake_B'] - save_path = render_dir + "frame_{:05d}_tmp.png".format(i+1) - final_path = render_dir + "frame_{:05d}.png".format(i+1) # s = 256 # p = 8 # im = imresize(im, (s-p, s-p), interp='bicubic') @@ -62,34 +64,43 @@ if __name__ == '__main__': # image_pil.save(save_path) # copyfile(save_path, final_path) if last_im is not None: - frac_a = 999/1000 - frac_b = 1/1000 + frac_a = 100/100 + frac_b = 0/100 tmp_im = im.copy() array_a = np.multiply(im, frac_a) array_b = np.multiply(last_im, frac_b) - # im = np.add(array_a, array_b).astype('int8') - # print(im.shape, im.dtype) - last_im = np.roll(tmp_im, 1, axis=1) - else: + im = np.add(array_a, array_b).astype('int8') + #print(im.shape, im.dtype) + last_im = tmp_im # np.roll(tmp_im, 1, axis=1) + elif i < 2: last_im = im.copy() print(im.shape, im.dtype) - image_pil = Image.fromarray(im, mode='RGB') - image_pil.save(save_path) - os.rename(save_path, final_path) + image_pil = Image.fromarray(im, mode='RGB') + # image_pil.filter(ImageFilter.SHARPEN) + image_pil = image_pil.resize((456,256), Image.ANTIALIAS) + image_pil.save(save_path) + os.rename(save_path, final_path) webpage.save() - os.remove(render_dir + "frame_00000.png") + if os.path.exists(render_dir + "frame_00000.png"): + os.remove(render_dir + "frame_00000.png") - cmd = ("/usr/bin/ffmpeg", "-i", render_dir + "frame_%05d.png", "-y", "-c:v", "libx264", "-vf", "fps=30", "-pix_fmt", "yuv420p", render_dir + opt.name + "_" + opt.experiment + ".mp4") + if opt.mov is not None: + filename = opt.mov + if not filename.endswith('.mp4'): + filename += '.mp4' + else: + filename = opt.name + "_" + opt.experiment + ".mp4" + cmd = ("ffmpeg", "-i", render_dir + "frame_%05d.png", "-y", "-c:v", "libx264", "-vf", "fps=30", "-pix_fmt", "yuv420p", mov_dir + filename) process = subprocess.Popen(cmd, stdout=subprocess.PIPE) output, error = process.communicate() print("________") - print("\n") - cmd = ("scp", render_dir + opt.name + "_" + opt.experiment + ".mp4", "jules@asdf.us:asdf/neural/") + cmd = ("scp", mov_dir + filename, "jules@asdf.us:asdf/neural/") process = subprocess.Popen(cmd, stdout=subprocess.PIPE) output, error = process.communicate() + print("https://asdf.us/neural/" + filename) print("\n") - print("https://asdf.us/neural/" + opt.name + "_" + opt.experiment + ".mp4") + |