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  1. README.md +8 -6
  2. app.py +93 -0
  3. cat1.jpeg +0 -0
  4. cat2.jpeg +0 -0
  5. cat3.jpeg +0 -0
  6. cat4.jpeg +0 -0
  7. index.html +18 -56
  8. packages.txt +1 -0
  9. requirements.txt +12 -0
  10. style.css +28 -0
README.md CHANGED
@@ -1,10 +1,12 @@
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  ---
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- title: Sportmodel1
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- emoji: 🖼️
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- colorFrom: yellow
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- colorTo: red
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- sdk: static
 
 
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  pinned: false
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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  ---
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+ title: Frame Interpolation
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+ emoji: 🐢
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+ colorFrom: blue
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+ colorTo: gray
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+ sdk: gradio
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+ sdk_version: 3.1.4
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+ app_file: app.py
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  pinned: false
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  ---
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
app.py ADDED
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+ import os
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+ import sys
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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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+ from PIL import Image
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+ import gradio as gr
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+ from huggingface_hub import snapshot_download
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+
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+ # Clone the repository and add the path
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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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+
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+ # Import after appending the path
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+ from eval import interpolator, util
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+
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+ def load_model(model_name):
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+ model = interpolator.Interpolator(snapshot_download(repo_id=model_name), None)
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+ return model
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+
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+ model_names = [
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+ "akhaliq/frame-interpolation-film-style",
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+ "NimaBoscarino/frame-interpolation_film_l1",
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+ "NimaBoscarino/frame_interpolation_film_vgg",
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+ ]
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+
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+ models = {model_name: load_model(model_name) for model_name in model_names}
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+
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+ ffmpeg_path = util.get_ffmpeg_path()
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+ mediapy.set_ffmpeg(ffmpeg_path)
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+
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+ def resize(width, img):
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+ img = Image.fromarray(img)
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+ wpercent = (width / float(img.size[0]))
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+ hsize = int((float(img.size[1]) * float(wpercent)))
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+ img = img.resize((width, hsize), Image.LANCZOS)
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+ return img
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+
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+ def resize_and_crop(img_path, size, crop_origin="middle"):
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+ img = Image.open(img_path)
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+ img = img.resize(size, Image.LANCZOS)
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+ return img
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+
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+ def resize_img(img1, img2_path):
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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_path,
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+ (img_target_size.size[0], img_target_size.size[1]), # set width and height to match img1
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+ crop_origin="middle"
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+ )
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+ img_to_resize.save('resized_img2.png')
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+
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+ def predict(frame1, frame2, times_to_interpolate, model_name):
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+ model = models[model_name]
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+
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+ frame1 = resize(1080, frame1)
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+ frame2 = resize(1080, frame2)
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+
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+ frame1.save("test1.png")
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+ frame2.save("test2.png")
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+
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+ resize_img("test1.png", "test2.png")
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+ input_frames = ["test1.png", "resized_img2.png"]
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+
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+ frames = list(
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+ util.interpolate_recursively_from_files(
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+ input_frames, times_to_interpolate, model))
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+
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+ mediapy.write_video("out.mp4", frames, fps=30)
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+ return "out.mp4"
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+
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+ title = "Sports model"
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+ description = "Wechat:Liesle1"
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+ article = ""
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+ examples = [
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+ ['cat3.jpeg', 'cat4.jpeg', 2, model_names[0]],
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+ ['cat1.jpeg', 'cat2.jpeg', 2, model_names[1]],
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+ ]
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+
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+ gr.Interface(
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+ fn=predict,
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+ inputs=[
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+ gr.Image(label="First Frame"),
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+ gr.Image(label="Second Frame"),
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+ gr.Number(label="Times to Interpolate", value=2),
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+ gr.Dropdown(label="Model", choices=model_names),
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+ ],
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+ outputs=gr.Video(label="Interpolated Frames"),
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+ title=title,
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+ description=description,
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+ article=article,
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+ examples=examples,
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+ ).launch()
cat1.jpeg ADDED
cat2.jpeg ADDED
cat3.jpeg ADDED
cat4.jpeg ADDED
index.html CHANGED
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- <!DOCTYPE html>
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  <html>
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- <head>
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- <meta charset="utf-8">
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- <meta name="viewport" content="width=device-width, initial-scale=1">
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- <title>Gradio-Lite: Serverless Gradio Running Entirely in Your Browser</title>
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- <meta name="description" content="Gradio-Lite: Serverless Gradio Running Entirely in Your Browser">
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-
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- <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
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- <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
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-
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- <style>
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- html, body {
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- margin: 0;
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- padding: 0;
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- height: 100%;
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- }
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- </style>
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- </head>
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- <body>
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- <gradio-lite>
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- <gradio-file name="app.py" entrypoint>
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- import gradio as gr
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-
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- from filters import as_gray
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-
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- def process(input_image):
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- output_image = as_gray(input_image)
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- return output_image
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-
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- demo = gr.Interface(
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- process,
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- "image",
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- "image",
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- examples=["lion.jpg", "logo.png"],
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- )
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-
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- demo.launch()
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- </gradio-file>
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-
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- <gradio-file name="filters.py">
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- from skimage.color import rgb2gray
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-
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- def as_gray(image):
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- return rgb2gray(image)
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- </gradio-file>
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-
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- <gradio-file name="lion.jpg" url="https://raw.githubusercontent.com/gradio-app/gradio/main/gradio/test_data/lion.jpg" />
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- <gradio-file name="logo.png" url="https://raw.githubusercontent.com/gradio-app/gradio/main/guides/assets/logo.png" />
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-
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- <gradio-requirements>
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- # Same syntax as requirements.txt
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- scikit-image
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- </gradio-requirements>
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- </gradio-lite>
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- </body>
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- </html>
 
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+ <!doctype html>
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  <html>
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+ <head>
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+ <meta charset="utf-8" />
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+ <meta name="viewport" content="width=device-width" />
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+ <title>My static Space</title>
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+ <link rel="stylesheet" href="style.css" />
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+ </head>
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+ <body>
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+ <div class="card">
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+ <h1>Welcome to your static Space!</h1>
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+ <p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
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+ <p>
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+ Also don't forget to check the
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+ <a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
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+ </p>
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+ </div>
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+ </body>
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+ </html>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
packages.txt ADDED
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+ ffmpeg
requirements.txt ADDED
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+ tensorflow>=2.6.2 # The latest should include tensorflow-gpu
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+ tensorflow-datasets>=4.4.0
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+ tensorflow-addons>=0.15.0
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+ absl-py>=0.12.0
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+ gin-config>=0.5.0
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+ parameterized>=0.8.1
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+ mediapy>=1.0.3
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+ scikit-image>=0.19.1
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+ apache-beam>=2.34.0
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+ google-cloud-bigquery-storage>=1.1.0 # Suppresses a harmless error from beam
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+ natsort>=8.1.0
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+ image-tools
style.css ADDED
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+ body {
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+ padding: 2rem;
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+ font-family: -apple-system, BlinkMacSystemFont, "Arial", sans-serif;
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+ }
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+
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+ h1 {
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+ font-size: 16px;
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+ margin-top: 0;
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+ }
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+
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+ p {
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+ color: rgb(107, 114, 128);
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+ font-size: 15px;
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+ margin-bottom: 10px;
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+ margin-top: 5px;
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+ }
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+
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+ .card {
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+ max-width: 620px;
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+ margin: 0 auto;
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+ padding: 16px;
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+ border: 1px solid lightgray;
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+ border-radius: 16px;
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+ }
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+
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+ .card p:last-child {
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+ margin-bottom: 0;
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+ }