Update app.py

app.py

@@ -1,29 +1,29 @@
-from fastapi import FastAPI, UploadFile
-from fastapi.responses import JSONResponse
+import gradio as gr
 from PIL import Image
 import torch
-from torchvision import transforms
 from transformers import ViTFeatureExtractor, ViTForImageClassification
-import io
-
-app = FastAPI()
 
 # Load model + processor
 model = ViTForImageClassification.from_pretrained("Falconsai/nsfw_image_detection")
 processor = ViTFeatureExtractor.from_pretrained("Falconsai/nsfw_image_detection")
 
-transform = transforms.Compose([
-    transforms.Resize((224, 224)),
-    transforms.ToTensor()
-])
-
-@app.post("/predict/")
-async def predict(file: UploadFile):
-    image = Image.open(io.BytesIO(await file.read())).convert("RGB")
+def predict(image):
+    # Process image
     inputs = processor(images=image, return_tensors="pt")
     with torch.no_grad():
         outputs = model(**inputs)
         logits = outputs.logits
         predicted_class_idx = logits.argmax(-1).item()
         label = model.config.id2label[predicted_class_idx]
-    return JSONResponse({"label": label})
+    return label
+
+# Gradio Interface
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", label="Upload Image"),
+    outputs=gr.Label(label="Prediction"),
+    title="NSFW Image Detection (ViT)",
+    description="Upload an image to classify if it's NSFW or SFW."
+)
+
+demo.launch()