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import marimo |
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__generated_with = "0.17.0" |
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app = marimo.App() |
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@app.cell |
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def _(): |
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from open_clip import create_model_from_pretrained |
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import torch |
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from transformers import CLIPImageProcessor, AutoImageProcessor |
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from urllib.request import urlopen |
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from PIL import Image |
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return ( |
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AutoImageProcessor, |
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CLIPImageProcessor, |
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Image, |
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create_model_from_pretrained, |
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torch, |
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urlopen, |
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) |
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@app.cell |
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def _(Image, urlopen): |
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image = Image.open(urlopen( |
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'https://media.gettyimages.com/id/1309385864/photo/las-vegas-strip-skyline-landscaped-ultra-wide-shot-at-night.jpg?s=1024x1024&w=gi&k=20&c=bBxkjq8FoK2bPKYLtqbJMCgpsvjUm-vI7-yw04cq7AU=' |
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)) |
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image.size |
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return (image,) |
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@app.cell |
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def _(): |
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model = "apple/DFN5B-CLIP-ViT-H-14" |
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return (model,) |
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@app.cell |
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def _( |
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AutoImageProcessor, |
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CLIPImageProcessor, |
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create_model_from_pretrained, |
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model, |
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): |
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try: |
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hf_pre = AutoImageProcessor.from_pretrained(model) |
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except: |
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print("Auto image processor not found") |
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hf_pre = CLIPImageProcessor() |
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hf_pre_fix = CLIPImageProcessor( |
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do_center_crop=False, |
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do_normalize=True, |
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do_resize=True, |
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feature_extractor_type="CLIPFeatureExtractor", |
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image_mean=[ |
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0.48145466, |
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0.4578275, |
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0.40821073 |
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], |
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image_std=[ |
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0.26862954, |
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0.26130258, |
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0.27577711 |
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], |
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size={"width": 224, "height": 224}, |
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do_convert_rgb=True |
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) |
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_, preprocess = create_model_from_pretrained(f'hf-hub:{model}') |
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preprocess |
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return hf_pre, hf_pre_fix, preprocess |
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@app.cell |
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def _(hf_pre, hf_pre_fix, image, preprocess, torch): |
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hf_res_fix = torch.tensor(hf_pre_fix(images=image)["pixel_values"]).squeeze() |
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hf_res = torch.tensor(hf_pre(images=image)["pixel_values"]).squeeze() |
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op_res = preprocess(image) |
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op_res.shape, hf_res.shape |
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return hf_res, hf_res_fix, op_res |
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@app.cell |
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def _(hf_res, op_res): |
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(hf_res == op_res).all() |
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return |
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@app.cell |
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def _(hf_res_fix, op_res): |
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(hf_res_fix == op_res).all() |
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return |
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@app.cell |
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def _(hf_res, hf_res_fix, image, op_res): |
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import matplotlib.pyplot as plt |
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fig, axs = plt.subplots(1, 4, figsize=(15, 5)) |
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axs[0].imshow(image) |
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axs[0].set_title("Original Image") |
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axs[1].imshow(op_res.permute(1, 2, 0).numpy()) |
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axs[1].set_title("OpenCLIP Preprocessed Image") |
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axs[2].imshow(hf_res.permute(1, 2, 0).numpy()) |
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axs[2].set_title("HuggingFace Preprocessed Image") |
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axs[3].imshow(hf_res_fix.permute(1, 2, 0).numpy()) |
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axs[3].set_title("HuggingFace FIXED Preprocessed Image") |
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plt.show() |
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return |
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@app.cell |
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def _(hf_pre_fix): |
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hf_pre_fix.to_json_file("test.json") |
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return |
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@app.cell |
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def _(): |
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return |
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if __name__ == "__main__": |
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app.run() |
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