Update app.py

app.py

@@ -6,7 +6,6 @@ from PIL import Image
 import requests
 import base64
 from io import BytesIO
-import os
 
 # Define the number of classes
 num_classes = 2  # Update with the actual number of classes in your dataset
@@ -34,23 +33,16 @@ transform = transforms.Compose([
 ])
 
 # Prediction function
-def process_image(data):
+def process_image(image, image_url=None):
     try:
-        # Check if the input contains a base64-encoded string
-        if isinstance(data, dict):
-            if "data" in data:
-                # Base64 decoding
-                image_data = base64.b64decode(data["data"])
-                image = Image.open(BytesIO(image_data))
-            elif "url" in data:
-                # URL-based image loading
-                response = requests.get(data["url"])
-                image = Image.open(BytesIO(response.content))
-            elif "path" in data:
-                # Local path image loading
-                image = Image.open(data["path"])
-            else:
-                return "Invalid input data structure."
+        # Handle URL-based image loading
+        if image_url:
+            response = requests.get(image_url)
+            image = Image.open(BytesIO(response.content))
+
+        # Handle local file path image loading (Gradio File input)
+        elif isinstance(image, str) and os.path.isfile(image):
+            image = Image.open(image)
 
         # Validate image
         if not isinstance(image, Image.Image):
@@ -77,11 +69,14 @@ def process_image(data):
 # Create the Gradio interface
 iface = gr.Interface(
     fn=process_image,
-    inputs=gr.JSON(label="Upload an image (URL or Local Path)"),  # Input: JSON to handle URL or path
+    inputs=[
+        gr.File(label="Upload an image (Local File Path)"),  # Input: Local file
+        gr.Textbox(label="Enter Image URL", placeholder="Enter image URL here (optional)", optional=True)  # Input: Image URL (optional)
+    ],
     outputs=gr.Textbox(label="Prediction Result"),  # Output: Prediction result
     live=True,
     title="Maize Anomaly Detection",
-    description="Upload an image of maize to detect anomalies like disease or pest infestation. You can provide local paths, URLs, or base64-encoded images."
+    description="Upload an image of maize to detect anomalies like disease or pest infestation. You can upload local images or provide an image URL."
 )
 
 # Launch the Gradio interface