Update app.py

app.py

@@ -50,31 +50,32 @@ def resize_img(img1, img2_path):
     )
     img_to_resize.save('resized_img2.png')
 
-def predict(frame1, frame2, times_to_interpolate, model_name):
+def predict(frame1, frame2, frame3, frame4, times_to_interpolate, model_name):
     model = models[model_name]
 
-    frame1 = resize(1080, frame1)
-    frame2 = resize(1080, frame2)
+    frames = [resize(1080, frame) for frame in [frame1, frame2, frame3, frame4]]
 
-    frame1.save("test1.png")
-    frame2.save("test2.png")
+    for i, frame in enumerate(frames):
+        frame.save(f"test{i+1}.png")
 
-    resize_img("test1.png", "test2.png")
-    input_frames = ["test1.png", "resized_img2.png"]
+    interpolated_frames = []
 
-    frames = list(
-        util.interpolate_recursively_from_files(
-            input_frames, times_to_interpolate, model))
+    for i in range(3):
+        resize_img(f"test{i+1}.png", f"test{i+2}.png")
+        input_frames = [f"test{i+1}.png", "resized_img2.png"]
+        interpolated_frames.extend(
+            util.interpolate_recursively_from_files(
+                input_frames, times_to_interpolate, model))
 
-    mediapy.write_video("out.mp4", frames, fps=30)
+    mediapy.write_video("out.mp4", interpolated_frames, fps=30)
     return "out.mp4"
 
 title = "Sports model"
 description = "Wechat:Liesle1"
 article = ""
 examples = [
-    ['cat3.jpeg', 'cat4.jpeg', 2, model_names[0]],
-    ['cat1.jpeg', 'cat2.jpeg', 2, model_names[1]],
+    ['cat3.jpeg', 'cat4.jpeg', 'cat5.jpeg', 'cat6.jpeg', 2, model_names[0]],
+    ['cat1.jpeg', 'cat2.jpeg', 'cat3.jpeg', 'cat4.jpeg', 2, model_names[1]],
 ]
 
 gr.Interface(
@@ -82,6 +83,8 @@ gr.Interface(
     inputs=[
         gr.Image(label="First Frame"),
         gr.Image(label="Second Frame"),
+        gr.Image(label="Third Frame"),
+        gr.Image(label="Fourth Frame"),
         gr.Number(label="Times to Interpolate", value=2),
         gr.Dropdown(label="Model", choices=model_names),
     ],