crop-thirds

1 files changed, 96 insertions, 0 deletions

diff --git a/crop-thirds.py b/crop-thirds.py
new file mode 100644
index 0000000..34f2336
--- /dev/null
+++ b/crop-thirds.py
@@ -0,0 +1,96 @@
+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")
+# The default is a 24 degree overlap (equivalent to 1/6 of the 3:1 output image)
+# Setting a higher overlap means you can have taller vertical FOV.
+
+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=512)
+# 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('--aspect', type=float, default=3.0)
+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()
+
+src_width = 1024
+src_height = 512
+
+dst_width = int(src_width / opt.count)
+dst_height = int(dst_width / opt.aspect)
+dst_size = (dst_width, dst_height,)
+
+offsets = []
+
+for i in range(count):
+  offsets.append(int(i / count * dst_width))
+
+y0 = opt.vertical_offset - dst_height / 2
+
+crops = [(x, y0, x + dst_width, d0 + dst_height,) for x in offsets]
+letters = ['a', 'b', 'c']
+labels = [opt.label + '_' + letter for letter in letters]
+paths = [os.path.join(opt.out_dir, label) for label in labels]
+
+for path in paths:
+  if opt.clobber:
+      if os.path.exists(path):
+        rmtree(path)
+  os.makedirs(path)
+
+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(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))
+
+  canvas = Image.new('RGB', (int(src_width * 3/2), src_height,))
+  image = Image.open(fn)
+  canvas.paste(image, (0, 0))
+  canvas.paste(image, (src_width, 0))
+
+  for n, path in enumerate(paths):
+    canvas.crop(crops[n]).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
+#     ])
+