Update app.py

app.py

@@ -2,30 +2,50 @@ import gradio as gr
 import torch
 from PIL import Image
 from torchvision import transforms
+import huggingface_hub as hf
 
-# Hugging Face model
+# HuggingFace model and Spaces
 model = torch.hub.load('facebookresearch/deit:main', 'deit_tiny_patch16_224')
+repo = "uploader"
 
-# File upload component
-file = gr.FileInput()
+# File upload component with local or remote option
+file = gr.FileInput(type="file", label="Upload Image File", preview=True)
 
-# Display image
+# Display image 
 image = gr.Image(label="Uploaded Image")
 
+# Upload file to HuggingFace Spaces
+def upload_to_hf(filename):
+  with open(filename, 'rb') as f:
+    data = f.read()
+  hf.upload_file(data, f"/{repo}/{filename}")
+  return f"/{repo}/{filename}"
+
 # Run model on image
 def run(file):
-  image = Image.open(file).convert('RGB')
+  if file.startswith("http"): # remote file
+    filename = file.split("/")[-1]
+    filepath = upload_to_hf(filename)
+  else: # local file
+    filepath = file
+
+  image = Image.open(filepath).convert('RGB')
+
+  # preprocess, run model, return output
   transform = transforms.Compose([
-    transforms.Resize(256),
+    transforms.Resize(256), 
     transforms.CenterCrop(224),
     transforms.ToTensor(),
-    transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
+    transforms.Normalize([0.5,0.5,0.5],[0.5,0.5,0.5])  
   ])
+
   tensor = transform(image)
-  tensor = tensor.unsqueeze(0) 
+  tensor = tensor.unsqueeze(0)
+
   with torch.no_grad():
-      output = model(tensor)
-  image.update(file)
+    output = model(tensor)
+
+  image.update(filepath)
   return image
 
 # Launch app