Rounak28 commited on
Commit
f20e7b8
1 Parent(s): 6497665
Files changed (5) hide show
  1. .gitignore +7 -0
  2. app.py +38 -3
  3. model.py +18 -0
  4. models/model.pth +3 -0
  5. requirements.txt +1 -0
.gitignore ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
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+ .ipynb_checkpoints
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+ .vscode
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+ data
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+ data/training
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+ data/testing
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+ __pycache__
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+ nb.ipynb
app.py CHANGED
@@ -1,7 +1,42 @@
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  import gradio as gr
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- def greet(name):
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- return "Hello " + name + "!!"
 
 
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- iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  iface.launch()
 
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  import gradio as gr
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+ import torch
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+ from torch.nn import Softmax
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+ from torchvision.io import read_image
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+ from torchvision.transforms.functional import rgb_to_grayscale
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+ from model import NeuralNet
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+
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+ device = "cuda" if torch.cuda.is_available() else "cpu"
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+
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+ model = NeuralNet().to(device)
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+ model.load_state_dict(torch.load("models/model.pth"))
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+
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+
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+ labels = [
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+ "zero",
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+ "one",
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+ "two",
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+ "three",
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+ "four",
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+ "five",
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+ "six",
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+ "seven",
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+ "eight",
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+ "nine"
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+ ]
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+
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+ def predict(image):
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+ img = read_image(image).to(device)
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+ img = rgb_to_grayscale(img) / 255
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+ pred = model(img)[0]
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+ prob = Softmax(dim=0)(pred).tolist()
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+ return {l:p for l, p in zip(labels, prob)}
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+
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+
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+ iface = gr.Interface(
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+ fn=predict,
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+ inputs=gr.Image(label="Upload", type="filepath", shape=(28, 28)),
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+ outputs=gr.Label(num_top_classes=10),
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+ )
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  iface.launch()
model.py ADDED
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+ import torch.nn as nn
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+
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+ class NeuralNet(nn.Module):
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+ def __init__(self):
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+ super().__init__()
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+ self.flatten = nn.Flatten()
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+ self.layers = nn.Sequential(
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+ nn.Linear(28*28, 512),
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+ nn.ReLU(),
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+ nn.Linear(512, 512),
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+ nn.ReLU(),
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+ nn.Linear(512, 10)
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+ )
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+
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+ def forward(self, x):
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+ x = self.flatten(x)
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+ x = self.layers(x)
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+ return x
models/model.pth ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:f1d2226400fd63af4ccf83ed5c9f937cbe87ab5775bd42199f5270dc8da14acb
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+ size 2680775
requirements.txt ADDED
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+ torch