crop moving

1 files changed, 108 insertions, 0 deletions

diff --git a/crop-moving.py b/crop-moving.py
new file mode 100644
index 0000000..1f4e69a
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+++ b/crop-moving.py
@@ -0,0 +1,108 @@
+import os
+import glob
+import argparse
+from shutil import rmtree
+from PIL import Image
+from multiprocessing import Pool, cpu_count
+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")
+
+parser = argparse.ArgumentParser()
+parser.add_argument('--folder', default="./results/wood/")
+parser.add_argument('--out_dir', default="./thirds/")
+parser.add_argument('--label', required=True)
+parser.add_argument('--vertical_offset', type=int, default=256)
+# parser.add_argument('--dst_width', type=int, default=1024)
+# parser.add_argument('--dst_height', type=int, default=512)
+parser.add_argument('--count', type=int, default=3)
+parser.add_argument('--max', type=int, default=99997)
+parser.add_argument('--crop_aspect', type=float, default=1.5)
+parser.add_argument('--aspect', type=float, default=2.0)
+# parser.add_argument('--folder_id', type=int, required=True)
+parser.add_argument('--margin', type=int, default=16)
+parser.add_argument('--no_clobber', action='store_false')
+opt = parser.parse_args()
+
+src_width = 1024
+src_height = 512
+
+dst_width = int(src_width / opt.count)
+dst_height = int(dst_width / opt.aspect)
+
+crop_width = dst_width
+crop_height = int(dst_width / opt.aspect * opt.crop_aspect)
+
+x_margin = opt.margin
+y_margin = opt.margin * opt.crop_aspect
+
+crop_size = (crop_width, crop_height,)
+dst_size = (dst_width + opt.margin * 2, dst_height + opt.margin * 2,)
+y0 = opt.vertical_offset - crop_height / 2 - y_margin
+
+crops = []
+paths = []
+out_path = os.path.join(opt.out_dir, opt.label)
+
+if not opt.no_clobber:
+  if os.path.exists(out_path):
+    rmtree(out_path)
+
+for i in range(opt.count):
+  x = int(i / opt.count * src_width) - x_margin
+  w = x + crop_width + x_margin + x_margin
+  if w > src_width:
+    w = src_width
+    x = src_width - (crop_width + x_margin + x_margin)
+  if x < 0:
+    x = 0
+  crops.append((x, y0, w, y0 + crop_height + y_margin + y_margin,))
+  path = os.path.join(out_path, chr(97 + i))
+  os.makedirs(path)
+  paths.append(path)
+
+max_i = opt.max
+dataset = []
+for i, fn in enumerate(sorted(glob.glob(os.path.join(opt.folder, '*.png')))):
+  if i >= max_i:
+    break
+  out_fn = "frame_{:05d}.png".format(i + 1)
+  if opt.no_clobber and os.path.exists(os.path.join(paths[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))
+
+  image = Image.open(fn)
+
+  ii = i % (crop_width + x_margin + x_margin)
+  crop = (ii, y0, ii + crop_width + x_margin + x_margin, y0 + crop_height + y_margin + y_margin)
+  image.crop(crops[n]).resize(dst_size).save(os.path.join(path, out_fn))
+
+chunksize = 3
+with Pool(processes=cpu_count()) as pool:
+  pool.starmap(build_thumbnail, dataset, chunksize)
+
+# if opt.folder_id > 0:
+#   endpoint = os.getenv('API_REMOTE') + '/api/file/'
+#   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
+#     ])