A new gradio app

app.py

@@ -0,0 +1,29 @@
+import gradio as gr 
+
+# def image_to_base64_str(pil_image):
+#     byte_arr = io.BytesIO()
+#     pil_image.save(byte_arr, format='PNG')
+#     byte_arr = byte_arr.getvalue()
+#     return str(base64.b64encode(byte_arr).decode('utf-8'))
+
+# def captioner(image):
+#     base64_image = image_to_base64_str(image)
+#     result = get_completion(base64_image)
+#     return result[0]['generated_text']
+
+from transformers import pipeline
+import gradio as gr
+
+pipeline = pipeline("image-classification", model="google/vit-base-patch16-224")
+gr.Interface.from_pipeline(pipeline).launch()
+
+gr.close_all()
+# demo = gr.Interface(fn=captioner,
+#                     inputs=[gr.Image(label="Upload image", type="pil")],
+#                     outputs=[gr.Textbox(label="Caption")],
+#                     title="Image Captioning with BLIP",
+#                     description="Caption any image using the BLIP model",
+#                     allow_flagging="never",
+#                     examples=["christmas_dog.jpeg", "bird_flight.jpeg", "cow.jpeg"])
+
+# demo.launch(share=True, server_port=int(os.environ['PORT1']))