Update app.py

app.py

@@ -3,7 +3,7 @@ import tensorflow as tf
 import numpy as np
 from PIL import Image
 
-# Load model
+# Load the trained model
 model = tf.keras.models.load_model("fashion_classifier_model.keras")
 
 # Class labels and tips
@@ -16,19 +16,19 @@ tips = {
     "traditional": "💡 Colorful bangles or a bright dupatta will complete your ethnic glam."
 }
 
-# Prediction logic
-def predict_style(file):
-    image = Image.open(file).resize((224, 224)).convert("RGB")
-    img_array = np.expand_dims(np.array(image) / 255.0, axis=0)
-    prediction = model.predict(img_array)
+# Prediction function (filepath version for mobile upload fix)
+def predict_style(image_path):
+    image = Image.open(image_path).resize((224, 224)).convert("RGB")
+    image_array = np.expand_dims(np.array(image) / 255.0, axis=0)
+    prediction = model.predict(image_array)
     index = np.argmax(prediction)
     label = class_names[index].upper()
     confidence = prediction[0][index] * 100
     result = f"<div class='result-box'><h2>👑 Your Style Match: {label}</h2><p>📊 Confidence: {confidence:.2f}%</p></div>"
-    tip = f"<div class='tip-box'>{tips[class_names[index]]}</div>"
-    return result, tip
+    style_tip = f"<div class='tip-box'>{tips[class_names[index]]}</div>"
+    return result, style_tip
 
-# Gradio Interface with Mobile-Compatible Upload
+# Gradio interface
 with gr.Blocks(css="""
 .result-box {
   background-color: #fff0f5;
@@ -77,13 +77,13 @@ body, .gradio-container {
 
     with gr.Row():
         with gr.Column():
-            file = gr.File(label="📸 Upload your outfit (image file)", file_types=["image"])
+            img = gr.Image(label="📸 Upload your outfit (for women)", type="filepath", image_mode="RGB")
             btn = gr.Button("✨ Detect My Style")
         with gr.Column():
             result = gr.HTML()
             tip = gr.HTML()
 
-    btn.click(fn=predict_style, inputs=file, outputs=[result, tip])
+    btn.click(predict_style, inputs=img, outputs=[result, tip])
 
     gr.Markdown("---")
     gr.Markdown("<p style='text-align:center;'>🧵 Made with 💖 by <a href='https://github.com/subata24' target='_blank'>Subata</a> | Powered by TensorFlow + Gradio</p>")