Duplicate from kazuk/image-to-video-film

Co-authored-by: Kazuki Nakayashiki <[email protected]>

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README.md

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+---
+title: Images to Video
+emoji: 👁
+colorFrom: pink
+colorTo: green
+sdk: gradio
+sdk_version: 3.16.1
+app_file: app.py
+pinned: false
+license: unknown
+duplicated_from: kazuk/image-to-video-film
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from transformers import pipeline
+import io, base64
+from PIL import Image
+import numpy as np
+import tensorflow as tf
+import mediapy
+import os
+import sys
+from huggingface_hub import snapshot_download
+from image_tools.sizes import resize_and_crop
+
+os.system("git clone https://github.com/google-research/frame-interpolation")
+sys.path.append("frame-interpolation")
+from eval import interpolator, util
+
+ffmpeg_path = util.get_ffmpeg_path()
+mediapy.set_ffmpeg(ffmpeg_path)
+
+model = snapshot_download(repo_id="akhaliq/frame-interpolation-film-style")
+interpolator = interpolator.Interpolator(model, None)
+
+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, output_name):
+    img_target_size = Image.open(img1)
+    img_to_resize = resize_and_crop(
+        img2,
+        (img_target_size.size[0], img_target_size.size[1]),
+        crop_origin="middle"
+    )
+    img_to_resize.save(output_name)
+
+def generate_interpolation(frame1, frame2, frame3, frame4, frame5, frame6, times_to_interpolate, fps):
+
+    frame1 = resize(256, frame1)
+    frame2 = resize(256, frame2)
+    frame3 = resize(256, frame3)
+    frame4 = resize(256, frame4)
+    frame5 = resize(256, frame5)
+    frame6 = resize(256, frame6)
+
+    frame1.save("test1.png")
+    frame2.save("test2.png")
+    frame3.save("test3.png")
+    frame4.save("test4.png")
+    frame5.save("test5.png")
+    frame6.save("test6.png")
+
+    resize_img("test1.png", "test2.png", "resized_img2.png")
+    resize_img("test1.png", "test3.png", "resized_img3.png")
+    resize_img("test1.png", "test4.png", "resized_img4.png")
+    resize_img("test1.png", "test5.png", "resized_img5.png")
+    resize_img("test1.png", "test6.png", "resized_img6.png")
+
+    input_frames = ["test1.png", "resized_img2.png", "resized_img3.png", "resized_img4.png", "resized_img5.png", "resized_img6.png"]
+
+    frames = list(util.interpolate_recursively_from_files(input_frames, times_to_interpolate, interpolator))
+
+    mediapy.write_video("out.mp4", frames, fps=fps)
+    
+    return "out.mp4"
+
+demo = gr.Blocks()
+
+with demo:
+    with gr.Row():
+    
+        # Left column (inputs)
+        with gr.Column():
+
+            with gr.Row():
+                # upload images and get image strings
+                input_arr = [
+                    gr.inputs.Image(type='filepath', label="Frame 1"),
+                    gr.inputs.Image(type='filepath', label="Frame 2"),
+                    gr.inputs.Image(type='filepath', label="Frame 3"),
+                    gr.inputs.Image(type='filepath', label="Frame 4"),
+                    gr.inputs.Image(type='filepath', label="Frame 5"),
+                    gr.inputs.Image(type='filepath', label="Frame 6"),
+                ]
+
+            with gr.Row():
+                input_arr.append(gr.inputs.Slider(minimum=2, maximum=10, step=1, label="Times to Interpolate"))
+                input_arr.append(gr.inputs.Slider(minimum=15, maximum=60, step=1, label="fps"))
+                        
+            # Rows of instructions & buttons
+            with gr.Row():
+                gr.Markdown("After uploading some images, hit the 'Generate Video' button to create a short video!")
+                button_gen_video = gr.Button("Generate Video")
+
+                
+        # Right column (outputs)
+        with gr.Column():
+            output_interpolation = gr.Video(label="Generated Video")
+            
+    # Bind functions to buttons
+    button_gen_video.click(fn=generate_interpolation, inputs=input_arr, outputs=output_interpolation)
+
+demo.launch(debug=True, enable_queue=True)

packages.txt

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+ffmpeg

requirements.txt

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+transformers
+torch
+
+tensorflow==2.11.0
+tensorflow-gpu==2.11.0
+tensorflow-datasets==4.4.0
+tensorflow-addons==0.15.0
+absl-py==1.4.0
+gin-config==0.5.0
+parameterized==0.8.1
+mediapy==1.0.3
+scikit-image==0.19.1
+apache-beam==2.34.0
+google-cloud-bigquery-storage==1.1.0
+natsort==8.1.0
+image-tools