Initial commit

app.py

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+import numpy as np
+import torch
+from pathlib import Path
+import torch.nn as nn
+import torch.nn.functional as F
+from PIL import Image
+from torchvision import transforms
+import gradio as gr
+
+
+transform = transforms.Compose([
+    transforms.Resize((28, 28)),
+    transforms.Grayscale(),
+    transforms.ToTensor()
+])
+labels = ["๐ (ศูนย์)", "๑ (หนึ่ง)", "๒ (สอง)", "๓ (สาม)", "๔ (สี่)", "๕ (ห้า)", "๖ (หก)", "๗ (เจ็ด)", "๘ (แปด)", "๙ (เก้า)"]
+LABELS = {i:k for i, k in enumerate(labels)} # dictionary of index and label
+
+
+# Load model using DropoutThaiDigit instead
+class DropoutThaiDigit(nn.Module):
+    def __init__(self):
+        super(DropoutThaiDigit, self).__init__()
+        self.fc1 = nn.Linear(28 * 28, 392)
+        self.fc2 = nn.Linear(392, 196)
+        self.fc3 = nn.Linear(196, 98)
+        self.fc4 = nn.Linear(98, 10)
+        self.dropout = nn.Dropout(0.1)
+        
+    def forward(self, x):
+        x = x.view(-1, 28 * 28)
+        x = self.fc1(x)
+        x = F.relu(x)
+        x = self.dropout(x)
+        x = self.fc2(x)
+        x = F.relu(x)
+        x = self.dropout(x)
+        x = self.fc3(x)
+        x = F.relu(x)
+        x = self.dropout(x)
+        x = self.fc4(x)
+        return x
+
+
+model = DropoutThaiDigit()
+model.load_state_dict(torch.load("thai_digit_net.pth"))
+model.eval()
+
+
+def predict(img):
+    """
+    Predict function takes image and return top 5 predictions
+    as a dictionary:
+
+        {label: confidence, label: confidence, ...}
+    """
+    if img is None:
+        return None
+    img = transform(img)  # do not need to use 1 - transform(img) because gradio already do it
+    probs = model(img).softmax(dim=1).ravel()
+    probs, indices = torch.topk(probs, 5)  # select top 5
+    probs, indices = probs.tolist(), indices.tolist()  # transform to list
+    confidences = {LABELS[i]: v for i, v in zip(indices, probs)}
+    return confidences
+
+
+gr.Interface(
+    fn=predict,
+    inputs="sketchpad",
+    outputs="label",
+    title="Thai Digit Handwritten Classification",
+    live=True
+).launch(enable_queue=True)

requirements.txt

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+torch

thai_digit_net.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4b9496e0d1c715adb46e7f30ba3791b95b589c45df168f7566cf3d96d54f3454
+size 1622805