Update app.py

app.py

@@ -1,34 +1,26 @@
 import gradio as gr
 from fastai.vision.all import *
 
-# Load the trained model
+# Load the exported model
 learn = load_learner('clocker.pkl')
 
-def guess_if_she_is_trans(img):
-    # Predict if the woman is transgender
-    pred, _, probs = learn.predict(img)
-    
-    # Create definitions for gender probability
-    transgender_probs = {learn.dls.vocab[i]: float(probs[i]) for i in range(len(learn.dls.vocab))}
-    
-    # Return the predicted gender and probabilities
-    return pred, transgender_probs
+def classify_image(img):
+    # Make a prediction
+    pred, idx, probs = learn.predict(img)
+    return {
+        "average woman": float(probs[0]),
+        "transgender woman": float(probs[1])
+    }
 
 # Create the Gradio interface
-demo = gr.Interface(
-    fn=guess_if_she_is_trans,
-    inputs=gr.Image(type="pil"),
-    outputs=[
-        gr.Label(num_top_classes=1, label="My guess..."),
-        gr.Label(num_top_classes=5, label="Transfem probability")
-    ],
-    examples=[
-        ["average_woman.jpg"],
-        ["transgender_woman.jpg"]
-    ],
-    title="Transfem Clocker",
-    description="Upload a photo of a woman and this will guess if she's trans."
+iface = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(),
+    outputs=gr.Label(num_top_classes=2),
+    title="Woman Type Classifier",
+    description="Upload an image to classify whether it's an average woman or a transgender woman.",
+    examples=["average_woman.jpg"]
 )
 
 # Launch the interface
-demo.launch()
+iface.launch()