Spaces:
Running
Running
Jason Wu
commited on
Commit
•
aac647d
1
Parent(s):
31fe217
add initial files
Browse files- app.py +32 -0
- res/example.jpg +0 -0
- res/example_pair1.jpg +0 -0
- res/example_pair2.jpg +0 -0
app.py
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import torch
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import gradio as gr
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import json
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from torchvision import transforms
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import torch.nn.functional as F
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TORCHSCRIPT_PATH = "res/screensim-resnet-uda+web350k.torchscript"
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IMG_SIZE = (256, 128)
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model = torch.jit.load(TORCHSCRIPT_PATH)
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img_transforms = transforms.Compose([
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transforms.Resize(IMG_SIZE),
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transforms.ToTensor(),
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transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
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])
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def predict(img1, img2, thresh=0.35):
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img_input1 = img_transforms(img1).unsqueeze(0)
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img_input2 = img_transforms(img2).unsqueeze(0)
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diff = torch.linalg.norm(model(img_input1) - model(img_input2))
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return "{:.3f}".format(diff), "same screen" if float(diff) < thresh else "different screens"
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example_imgs = [
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["res/example_pair1.jpg", "res/example_pair2.jpg", 0.35],
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["res/example_pair1.jpg", "res/example.jpg", 0.35]
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]
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interface = gr.Interface(fn=predict, inputs=[gr.Image(type="pil"), gr.Image(type="pil"), gr.Slider(0.2, 0.5, step=0.05, value=0.35)], outputs=["text", "text"], examples=example_imgs)
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interface.launch()
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res/example.jpg
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res/example_pair1.jpg
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res/example_pair2.jpg
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