updated

app.py

@@ -78,6 +78,19 @@ def classify_eye_shape(image):
     formatted_output = {item['label']: item['score'] for item in output}
     
     return formatted_output
+
+def classify_eye_color(image):
+
+    pipe = pipeline("image-classification", model="justingrammens/eye-color")
+    
+    # Run the pipeline on the uploaded image
+    output = pipe(image)
+    
+    print("Pipeline output for eye color:", output)
+    # Format the output to be compatible with gr.outputs.Label
+    formatted_output = {item['label']: item['score'] for item in output}
+    
+    return formatted_output
     
     
 def classify_image_with_multiple_models(image):
@@ -87,8 +100,9 @@ def classify_image_with_multiple_models(image):
     acne_results = classify_acne_type(image)
     hair_color_results = classify_hair_color(image)
     eye_shape = classify_eye_shape(image)
+    eye_color = classify_eye_color(image)
 
-    return face_shape_result, age_result, skin_type_result, acne_results, hair_color_results, eye_shape
+    return face_shape_result, age_result, skin_type_result, acne_results, hair_color_results, eye_shape, eye_color
 
 
 # Create the Gradio interface
@@ -101,7 +115,8 @@ demo = gr.Interface(
         gr.Label(num_top_classes=3, label="Skin Type"), 
         gr.Label(num_top_classes=5, label="Acne Type"), 
         gr.Label(num_top_classes=5, label="Hair Color"), 
-        gr.Label(num_top_classes=4, label="Eye Shape")
+        gr.Label(num_top_classes=4, label="Eye Shape"),
+        gr.Label(num_top_classes=5, label="Eye Color"),
     ],
     title="Multiple Model Classification",
     description="Upload an image to classify the face using mutiple classification models"