Update app.py

app.py

@@ -14,6 +14,7 @@ import gradio as gr
 from huggingface_hub import snapshot_download
 
 from image_tools.sizes import resize_and_crop
+from moviepy.editor import *
 
 
 model = snapshot_download(repo_id="akhaliq/frame-interpolation-film-style")
@@ -23,94 +24,18 @@ interpolator = interpolator.Interpolator(model, None)
 ffmpeg_path = util.get_ffmpeg_path()
 mediapy.set_ffmpeg(ffmpeg_path)
 
-def resize(width,img):
-  basewidth = width
-  img = Image.open(img)
-  wpercent = (basewidth/float(img.size[0]))
-  hsize = int((float(img.size[1])*float(wpercent)))
-  img = img.resize((basewidth,hsize), Image.ANTIALIAS)
-  return img
-  
-
-def resize_img(img1,img2):
- img_target_size = Image.open(img1)
- img_to_resize = resize_and_crop(
-     img2, 
-     (img_target_size.size[0],img_target_size.size[1]), #set width and height to match img1
-     crop_origin="middle"
-     )
- img_to_resize.save('resized_img2.png')
-
-  
-sketch1 = gr.Image(image_mode="RGB",
-        source="canvas",
-        tool='color-sketch',
-        type="filepath",
-        shape=None,
-        invert_colors=False)
-
-sketch2 = gr.Image(image_mode="RGB",
-        source="canvas",
-        tool='color-sketch',
-        type="filepath",
-        shape=None,
-        invert_colors=False)
-
-slider = gr.inputs.Slider(minimum=2,maximum=4,step=1)
 
         
-def predict(frame1, frame2, times_to_interpolate):
-   
-    frame1 = resize(512,frame1)
-    frame2 = resize(512,frame2)
-
-    frame1.save("test1.png")
-    frame2.save("test2.png")
-
-    resize_img("test1.png","test2.png")
-    input_frames = ["test1.png", "resized_img2.png"]
+def interpolate(frame1, frame2, times_to_interpolate):
+    
+    input_frames = [frame1, frame2]
 
     frames = list(
         util.interpolate_recursively_from_files(
             input_frames, times_to_interpolate, interpolator))
     print(frames)  
-    mediapy.write_video("out.mp4", frames, fps=24)
-
-    # video.mp4 is a video of 9 seconds
-    filename = "out.mp4"
-        
-    cap = cv2.VideoCapture(filename)
-    cap.set(cv2.CAP_PROP_POS_AVI_RATIO,0)
-    frameCount = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-    frameWidth = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-    frameHeight = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-    videoFPS = int(cap.get(cv2.CAP_PROP_FPS))
-    
-    print (f"frameCount: {frameCount}")
-    print (f"frameWidth: {frameWidth}")
-    print (f"frameHeight: {frameHeight}")
-    print (f"videoFPS: {videoFPS}")
-    
-    buf = np.empty((
-        frameCount,
-        frameHeight,
-        frameWidth,
-        3), np.dtype('uint8'))
-    
-    fc = 0
-    ret = True
-    
-    while (fc < frameCount):
-        ret, buf[fc] = cap.read()
-        fc += 1
-    
-    cap.release()
-    videoArray = buf
-    
-    print (f"DURATION: {frameCount/videoFPS}")
-    print (videoArray)
-    
-    return "out.mp4", videoArray
+   
+    return "done"
     
     
     
@@ -119,4 +44,4 @@ description="<p style='text-align: center'>This is a fork of the Gradio demo for
 article = "<p style='text-align: center'><a href='https://film-net.github.io/' target='_blank'>FILM: Frame Interpolation for Large Motion</a> | <a href='https://github.com/google-research/frame-interpolation' target='_blank'>Github Repo</a></p>"
 custom_css = "style.css"
 
-gr.Interface(predict,[sketch1,sketch2,slider],outputs=[gr.Video(label="video output"),gr.Gallery(label="list of frames output").style(grid=5)],title=title,description=description,article=article,css=custom_css).launch(enable_queue=True)
+gr.Interface(interpolate,[gr.Image(source="upload", type="filepath"),gr.Image(source="upload", type="filepath"),2],outputs=[gr.Textbox()],title=title,description=description,article=article,css=custom_css).launch(enable_queue=True)