Create app.py

app.py

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+from transformers import pipeline
+from turtle import title
+import gradio as gr
+from transformers import pipeline
+import numpy as np
+from PIL import Image
+
+# More models in the model hub.
+checkpoint = "openai/clip-vit-large-patch14-336"
+classifier = pipeline("zero-shot-image-classification",
+                      model=checkpoint)
+
+
+def shot(image, labels_text):
+    PIL_image = Image.fromarray(np.uint8(image)).convert('RGB')
+    labels = labels_text.split(",")
+    res = classifier(images=PIL_image, 
+           candidate_labels=labels,
+           hypothesis_template= "This is a photo of a {}")
+    return {dic["label"]: dic["score"] for dic in res}
+    
+interface = gr.Interface(shot, 
+                     inputs=["image", "text"], 
+                     outputs="label",
+                    description="Add a picture and a list of labels separated by commas",
+                    examples=[['tundra.jpg', 'Ford F-150, RAM 1500, GMC Sierra, Silverado'],
+                              ['interior.jpeg', 'Interior,Exterior'],
+                              ['carplay.webp', 'Carplay, Android play']
+                    ]
+                    title="Zero-shot Image Classification")
+
+interface.launch()