Update app.py

app.py

@@ -1,39 +1,34 @@
-# Human Action Recognition
+# rvv-karma/Human-Action-Recognition
 
-## LOADING MODULES
 
+## Creating prediction pipeline
 
+from PIL import Image
 from transformers import pipeline
-# from PIL import Image
-# import requests
-import gradio as gr
-
 pipe = pipeline("image-classification", "rvv-karma/Human-Action-Recognition-VIT-Base-patch16-224")
 
 def classify_image(input):
+    image = Image.fromarray(input.astype('uint8'), 'RGB')
     predictions = pipe(image)
     return {prediction["label"]: prediction["score"] for prediction in predictions}
 
-    
-# Output:
-# [{'score': 0.9918079972267151, 'label': 'dancing'},
-#  {'score': 0.00207977625541389, 'label': 'clapping'},
-#  {'score': 0.0015223610680550337, 'label': 'running'},
-#  {'score': 0.0009153694845736027, 'label': 'fighting'},
-#  {'score': 0.0006987180095165968, 'label': 'sitting'}]
 
+import gradio as gr
 
 ex=[['cat2.jpg'],
     ['dog2.jpeg'],  
      ['cat3.jpg'],
      ['dog.jpeg']]
 
+ex = []
+
 """
 ## RUNNING WEB UI"""
 
-image = gr.inputs.Image()
-label = gr.outputs.Label(num_top_classes=5)
+image = gr.Image()
+label = gr.Label(num_top_classes=5)
 
-gr.Interface(fn=classify_image, inputs=image, outputs=label, title='Human Action Recognition',
-             height=600, width=1200, examples=ex, theme='peach').launch(debug=True)
+description = "Categories: " + "'" + "', '".join(pipe.model.config.label2id.keys()) + "'"
 
+gr.Interface(fn=classify_image, inputs=image, outputs=label, title='Human Action Recognition',
+             description=description, examples=ex, theme='peach').launch(height=1000, width=1600, debug=True)