v1

app.py

@@ -0,0 +1,36 @@
+import gradio as gr
+import torch
+from PIL import Image
+from torchvision.transforms import Compose, Resize, ToTensor, Normalize
+
+
+
+print('loading model..')
+model = torch.load('model.pth')
+model.eval()
+print('loaded.')
+
+
+transform = Compose([
+    Resize((300,300)),
+    ToTensor(),
+    Normalize(mean=[0.485, 0.456, 0.406],
+                        std=[0.229, 0.224, 0.225]),
+])
+
+def predict(img):
+    img = Image.fromarray(img.astype('uint8'), 'RGB')
+    img = transform(img)
+    img = img.unsqueeze(0)
+
+    prediction = model(img).argmax(axis=1)
+    return f'Model prediction is {prediction[0]}'
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=["image"],
+    outputs=["text"],
+)
+
+demo.launch()
+