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