Duplicate from nanomenta/sketch_frame_interpolation

.gitattributes

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+*.model filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+title: Sketch Frame Interpolation
+emoji: 🐠🐠
+colorFrom: blue
+colorTo: gray
+sdk: gradio
+sdk_version: 3.24.1
+app_file: app.py
+pinned: false
+duplicated_from: nanomenta/sketch_frame_interpolation
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import os
+os.system("git clone https://github.com/google-research/frame-interpolation")
+import sys
+sys.path.append("frame-interpolation")
+
+import cv2
+import numpy as np
+import tensorflow as tf
+import mediapy
+from PIL import Image
+from eval import interpolator, util
+import gradio as gr
+
+from huggingface_hub import snapshot_download
+
+from image_tools.sizes import resize_and_crop
+
+
+model = snapshot_download(repo_id="akhaliq/frame-interpolation-film-style")
+
+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"]
+
+    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
+    
+    
+    
+title="sketch-frame-interpolation"
+description="<p style='text-align: center'>This is a fork of the Gradio demo for FILM: Frame Interpolation for Large Scene Motion from @akhaliq, but using sketches instead of images. This could be very useful for the animation industry :) <br /> To use it, simply draw your sketches and add the times to interpolate number. Read more at the links below. <br /> <img id='visitor-badge' alt='visitor badge' src='https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.sketch_frame_interpolation' style='display: inline-block'/></p>"
+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)

packages.txt

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+ffmpeg

requirements.txt

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+tensorflow
+tensorflow-datasets
+tensorflow-addons
+absl-py
+gin-config
+parameterized
+mediapy
+opencv-python
+scikit-image
+apache-beam
+google-cloud-bigquery-storage # Suppresses a harmless error from beam
+natsort
+image-tools
+numpy

style.css

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+.h-60 {
+    height: 35rem;
+}