Update app.py

app.py

@@ -1,15 +1,26 @@
 import gradio as gr
 from transformers import pipeline
 
+# Initialize pipelines
 crop_pipe = pipeline("image-classification", model="LucyintheSky/pose-estimation-crop-uncrop")
+pose_pipe = pipeline("image-classification", model="LucyintheSky/pose-estimation-front-side-back")
+name_pipe = pipeline("image-classification", model="LucyintheSky/model-prediction")
 
 def classify(img):
+    # Classify image
     crop = crop_pipe(img)
-    result = crop[0]['label'] + ' (' + str(int(float(crop[0]['score']) * 100)) + '%)'
+    pose = pose_pipe(img)
+    name = name_pipe(img)
+    
+    # Format results
+    result = crop[0]['label'] + ' (' + str(int(float(crop[0]['score']) * 100)) + '%)\n'
+    result += pose[0]['label'] + ' (' + str(int(float(pose[0]['score']) * 100)) + '%)\n'
+    result += name[0]['label'] + ' (' + str(int(float(name[0]['score']) * 100)) + '%)'
+    
     return result
 
 iface = gr.Interface(fn=classify, 
                      inputs=gr.Image(label='Image', type='filepath'), 
-                     outputs=gr.Textbox(label='Output'), 
+                     outputs=gr.Textbox(label='Classification'), 
                      theme=gr.themes.Base(primary_hue=gr.themes.colors.pink, secondary_hue=gr.themes.colors.gray, neutral_hue=gr.themes.colors.slate, font=["avenir"]))
 iface.launch()