Upload app.py
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app.py
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# -*- coding: utf-8 -*-
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"""Pictionary_with_Gradio.ipynb
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Automatically generated by Colaboratory.
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Original file is located at
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https://colab.research.google.com/drive/17zR3z7tyss0M9EpMfcM7DSzG-WdE3-Kc
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"""
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import torch
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from torch import nn
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from pathlib import Path
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!pip3 install gradio
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LABELS=Path('class_names.txt').read_text().splitlines()
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model = nn.Sequential(
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nn.Conv2d(1, 32, 3, padding='same'),
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nn.ReLU(),
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nn.MaxPool2d(2),
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nn.Conv2d(32, 64, 3, padding='same'),
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nn.ReLU(),
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nn.MaxPool2d(2),
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nn.Conv2d(64, 128, 3, padding='same'),
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nn.ReLU(),
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nn.MaxPool2d(2),
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nn.Flatten(),
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nn.Linear(1152, 256),
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nn.ReLU(),
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nn.Linear(256, len(LABELS)),
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)
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state_dict=torch.load('pytorch_model.bin',map_location='cpu')
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import gradio as gr
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model.load_state_dict(state_dict, strict=False)
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model.eval()
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def predict(im):
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x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.
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with torch.no_grad():
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out = model(x)
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probabilities = torch.nn.functional.softmax(out[0], dim=0)
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values, indices = torch.topk(probabilities, 5)
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return {LABELS[i]: v.item() for i, v in zip(indices, values)}
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interface=gr.Interface(
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predict,
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inputs="sketchpad",
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outputs='label',
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theme="huggingface",
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title="Sketch Recognition",
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description="Sketch something for the model to guess in realtime",
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article = "<p style='text-align: center'>Sketch Recognition | Demo Model</p>",
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live=True)
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interface.launch(share=True)
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