Create app.py

app.py

@@ -0,0 +1,24 @@
+import os
+import gradio as gr
+from transformers import pipeline
+
+from transformers.utils import logging
+logging.set_verbosity_error()
+
+import warnings
+warnings.filterwarnings("ignore", 
+                        message="Using the model-agnostic default `max_length`")
+
+pipe = pipeline("image-to-text",
+                model="./models/Salesforce/blip-image-captioning-base")
+
+def launch(input):
+    out = pipe(input)
+    return out[0]['generated_text']
+
+iface = gr.Interface(launch,
+                     inputs=gr.Image(type='pil'),
+                     outputs="text")
+
+iface.launch(share=True, 
+             server_port=int(os.environ['PORT1']))