Update app.py

app.py

@@ -2,7 +2,6 @@ import gradio as gr
 import torch
 from PIL import Image
 from transformers import AutoModelForImageClassification, ViTImageProcessor
-import numpy as np
 
 # Load model
 model = AutoModelForImageClassification.from_pretrained("Falconsai/nsfw_image_detection")
@@ -10,15 +9,6 @@ processor = ViTImageProcessor.from_pretrained('Falconsai/nsfw_image_detection')
 
 # Function to make predictions
 def classify_image(img):
-    # Check if img is a NumPy array
-    if isinstance(img, np.ndarray):
-        # Convert NumPy array to PIL.Image.Image
-        img = Image.fromarray(img)
-
-    # Check if img is PIL.Image.Image
-    if not isinstance(img, Image.Image):
-        return "Error: Invalid image"
-
     with torch.no_grad():
         inputs = processor(images=img, return_tensors="pt")
         outputs = model(**inputs)
@@ -32,8 +22,12 @@ iface = gr.Interface(
     fn=classify_image,
     inputs="image",
     outputs="text",
-    live=True
+    live=True,
+    interpretation="default"
 )
 
 # Launch the Gradio Interface
-iface.launch(share=True)
+iface.launch()
+
+
+#gr.load("models/Falconsai/nsfw_image_detection").launch()