diff options
Diffstat (limited to 'crop-equirectangular.py')
| -rw-r--r-- | crop-equirectangular.py | 66 |
1 files changed, 53 insertions, 13 deletions
diff --git a/crop-equirectangular.py b/crop-equirectangular.py index 5927716..5222a59 100644 --- a/crop-equirectangular.py +++ b/crop-equirectangular.py @@ -3,6 +3,10 @@ import glob import argparse from shutil import rmtree from PIL import Image +from multiprocessing import Pool +from dotenv import load_dotenv, find_dotenv +import subprocess +load_dotenv(find_dotenv()) # This script generates crops with a specific aspect ratio from a 360 video. # It creates three sequences (identified by "--label") @@ -10,9 +14,10 @@ from PIL import Image # Setting a higher overlap means you can have taller vertical FOV. parser = argparse.ArgumentParser() -parser.add_argument('--folder', default="/media/ssd/sequences/venice_360/equi") +parser.add_argument('--folder', default="./pix2pixhd/sequences/venice_360/equi") parser.add_argument('--label', required=True) parser.add_argument('--vertical_offset', type=int, default=983) +parser.add_argument('--folder_id', type=int, required=True) parser.add_argument('--overlap', type=float, default=0.5) parser.add_argument('--clobber', action='store_false') opt = parser.parse_args() @@ -42,27 +47,39 @@ p0 = (x0, y0, x0 + crop_width, y0 + crop_height,) p1 = (x1, y0, x1 + crop_width, y0 + crop_height,) p2 = (x2, y0, x2 + crop_width, y0 + crop_height,) -path_0 = os.path.join("sequences", opt.label + "_a") -path_1 = os.path.join("sequences", opt.label + "_b") -path_2 = os.path.join("sequences", opt.label + "_c") +label_0 = opt.label + '_a' +label_1 = opt.label + '_b' +label_2 = opt.label + '_c' -if os.path.exists(path_0): - rmtree(path_0) -if os.path.exists(path_1): - rmtree(path_1) -if os.path.exists(path_2): - rmtree(path_2) +labels = [label_0, label_1, label_2] + +path_0 = os.path.join("sequences", label_0) +path_1 = os.path.join("sequences", label_1) +path_2 = os.path.join("sequences", label_2) + +if opt.clobber: + if os.path.exists(path_0): + rmtree(path_0) + if os.path.exists(path_1): + rmtree(path_1) + if os.path.exists(path_2): + rmtree(path_2) os.makedirs(path_0) os.makedirs(path_1) os.makedirs(path_2) -for i, fn in enumerate(glob.glob(os.path.join(opt.folder, '*.png'))): - if not opt.clobber and os.path.exists(path_0): +dataset = [] +for i, fn in enumerate(sorted(glob.glob(os.path.join(opt.folder, '*.png')))): + out_fn = "frame_{:05d}.png".format(i + 1) + if not opt.clobber and os.path.exists(os.path.join(path_0, out_fn)): continue + dataset.append((i, fn,)) + +def build_thumbnail(i, fn): + out_fn = "frame_{:05d}.png".format(i + 1) if (i % 100) == 0: print("{}...".format(i)) - out_fn = "frame_{:05d}.png".format(i + 1) canvas = Image.new('RGB', (int(src_width * 3/2), src_height,)) image = Image.open(fn) @@ -73,3 +90,26 @@ for i, fn in enumerate(glob.glob(os.path.join(opt.folder, '*.png'))): canvas.crop(p1).resize((1024, 512,), Image.ANTIALIAS).save(os.path.join(path_1, out_fn)) canvas.crop(p2).resize((1024, 512,), Image.ANTIALIAS).save(os.path.join(path_2, out_fn)) +agents = multiprocessing.cpu_count() +chunksize = 3 +with Pool(processes=agents) as pool: + pool.starmap(build_thumbnail, dataset, chunksize) + +if opt.folder_id > 0: + endpoint = os.getenv('API_REMOTE') + '/api/folder/{}/'.format(opt.folder_id) + for label in labels: + subprocess.call([ + "curl", + "-X", "POST", + "-d", "folder_id={}".format(opt.folder_id), + "-d", "module=pix2pixhd", + "-d", "name={}.mov".format(label), + "-d", "url=https://s3.amazonaws.com/i.asdf.us/cortex/lens/data/{}/{}.mov".format(opt.folder_id, label), + "-d", "dataset={}".format(label), + "-d", "activity=splice", + "-d", "generated=0", + "-d", "processed=1", + "-d", "datatype=video", + endpoint + ]) + |