fix film bugs

libs/film/predict.py

@@ -6,6 +6,7 @@ import tensorflow as tf
 import mediapy
 from PIL import Image
 import cog
+from huggingface_hub import snapshot_download
 
 from .eval import interpolator, util
 
@@ -16,20 +17,23 @@ class Predictor(cog.BasePredictor):
     def setup(self):
         import tensorflow as tf
         print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU')))
-        self.interpolator = interpolator.Interpolator("pretrained_models/film_net/Style/saved_model", None)
+
+        snapshot_download(repo_id="acmyu/FILM", local_dir="libs/film")
+
+        self.interpolator = interpolator.Interpolator("libs/film/pretrained_models/film_net/Style/saved_model", None)
 
         # Batched time.
         self.batch_dt = np.full(shape=(1,), fill_value=0.5, dtype=np.float32)
 
     
-    def predict(self, frame1, frame2, times_to_interpolate):
-        INPUT_EXT = ['.png', '.jpg', '.jpeg']
-        assert os.path.splitext(str(frame1))[-1] in INPUT_EXT and os.path.splitext(str(frame2))[-1] in INPUT_EXT, \
-            "Please provide png, jpg or jpeg images."
+    def predict(self, img1, img2, times_to_interpolate):
+        #INPUT_EXT = ['.png', '.jpg', '.jpeg']
+        #assert os.path.splitext(str(frame1))[-1] in INPUT_EXT and os.path.splitext(str(frame2))[-1] in INPUT_EXT, \
+        #    "Please provide png, jpg or jpeg images."
 
         # make sure 2 images are the same size
-        img1 = Image.open(str(frame1))
-        img2 = Image.open(str(frame2))
+        #img1 = Image.open(str(frame1))
+        #img2 = Image.open(str(frame2))
         if not img1.size == img2.size:
             img1 = img1.crop((0, 0, min(img1.size[0], img2.size[0]), min(img1.size[1], img2.size[1])))
             img2 = img2.crop((0, 0, min(img1.size[0], img2.size[0]), min(img1.size[1], img2.size[1])))