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Diffstat (limited to 'canny-cv.py')
| -rw-r--r-- | canny-cv.py | 129 |
1 files changed, 129 insertions, 0 deletions
diff --git a/canny-cv.py b/canny-cv.py new file mode 100644 index 0000000..df4526a --- /dev/null +++ b/canny-cv.py @@ -0,0 +1,129 @@ +import os +from options.test_options import TestOptions +from data import CreateRecursiveDataLoader +from models import create_model +from util.visualizer import Visualizer +from util.util import mkdirs, crop_image +from util import html +from shutil import move, copyfile +from PIL import Image, ImageOps +from skimage.transform import resize +from scipy.misc import imresize +from shutil import copyfile, rmtree +import numpy as np +import cv2 +import time + +import subprocess +from time import sleep + +blur = 3 +sigma = 0 +canny_lo = 10 +canny_hi = 220 +frac_a = 0.99 +frac_b = 1 - frac_a + +if __name__ == '__main__': + opt = TestOptions().parse() + opt.nThreads = 1 # test code only supports nThreads = 1 + opt.batchSize = 1 # test code only supports batchSize = 1 + opt.serial_batches = True # no shuffle + opt.no_flip = True # no flip + opt.experiment = opt.start_img.split("/")[-1].split(".")[0] + + render_dir = opt.results_dir + opt.name + "/exp:" + opt.experiment + "/" + + if os.path.exists(render_dir): + rmtree(render_dir) + mkdirs(render_dir) + + cmd = ("convert", opt.start_img, '-canny', '0x1+10%+30%', render_dir + "frame_00000.png") + process = subprocess.Popen(cmd, stdout=subprocess.PIPE) + output, error = process.communicate() + + #copyfile(opt.start_img, render_dir + "frame_00000.png") + + data_loader = CreateRecursiveDataLoader(opt) + dataset = data_loader.load_data() + ds = dataset.dataset + model = create_model(opt) + visualizer = Visualizer(opt) + # create website + web_dir = os.path.join(opt.results_dir, opt.name, '%s_%s' % (opt.phase, opt.which_epoch)) + webpage = html.HTML(web_dir, 'Experiment = %s, Phase = %s, Epoch = %s' % (opt.name, opt.phase, opt.which_epoch)) + # test + last_im = None + for i, data in enumerate(data_loader): + if i >= opt.how_many: + break + model.set_input(data) + model.test() + visuals = model.get_current_visuals() + 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) + if dataset.name() == 'RecursiveDatasetDataLoader': + # print(visuals.keys()) + im = visuals['fake_B'] + tmp_path = render_dir + "frame_{:05d}_tmp.png".format(i+1) + edges_path = render_dir + "frame_{:05d}.png".format(i+1) + render_path = render_dir + "ren_{:05d}.png".format(i+1) + # s = 256 + # p = 8 + # im = imresize(im, (s-p, s-p), interp='bicubic') + # image_pil = Image.fromarray(im) + # image_pil = ImageOps.expand(image_pil, p) + # image_pil.save(save_path) + # copyfile(save_path, final_path) + if last_im is not None: + tmp_im = im.copy() + #array_a = np.multiply(im.astype('float64'), frac_a) + #array_b = np.multiply(last_im.astype('float64'), frac_b) + #im = np.add(array_a, array_b).astype('uint8') + # print(im.shape, im.dtype) + last_im = np.roll(tmp_im, 1, axis=1) + else: + last_im = im.copy().astype('uint8') + tmp_im = im.copy().astype('uint8') + #print(im.shape, im.dtype) + + image_pil = Image.fromarray(tmp_im, mode='RGB') + image_pil.save(tmp_path) + os.rename(tmp_path, render_path) + + image_pil = Image.fromarray(im, mode='RGB') + image_pil = crop_image(image_pil, (0.50, 0.50), 0.5) + im = np.asarray(image_pil).astype('uint8') + #print(im.shape, im.dtype) + opencv_image = im[:, :, ::-1].copy() + opencv_image = cv2.GaussianBlur(opencv_image, (blur,blur), sigma) + opencv_image = cv2.Canny(opencv_image, canny_lo, canny_hi) + cv2.imwrite(tmp_path, opencv_image) + os.rename(tmp_path, edges_path) + + webpage.save() + + os.remove(render_dir + "frame_00000.png") + + t = time.time() + t /= 60 + t %= 525600 + video_fn = "{}_{}_canmix_{}frame_{}mix_{}blur_{}sigma_{}lo_{}hi_{}.mp4".format( + opt.name, opt.experiment, + opt.how_many, frac_a, + blur, sigma, canny_lo, canny_hi, + int(t)) + + cmd = ("/usr/bin/ffmpeg", "-i", render_dir + "ren_%05d.png", "-y", "-c:v", "libx264", "-vf", "fps=30", "-pix_fmt", "yuv420p", render_dir + video_fn) + process = subprocess.Popen(cmd, stdout=subprocess.PIPE) + output, error = process.communicate() + + print("________") + + cmd = ("scp", render_dir + video_fn, "jules@asdf.us:asdf/neural/") + process = subprocess.Popen(cmd, stdout=subprocess.PIPE) + output, error = process.communicate() + + print("https://asdf.us/neural/" + video_fn) + |