Create app.py

app.py

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+# Image Captioning from:
+# https://learn.deeplearning.ai/courses/open-source-models-hugging-face/lesson/12/image-captioning
+#
+
+from transformers import BlipForConditionalGeneration
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+
+from transformers import AutoProcessor
+processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+
+from PIL import Image
+import gradio as gr
+
+def captioning(input):
+    image_tensors = processor(input, return_tensors="pt")
+    image_text_tensors = model.generate(**image_tensors)
+    output = processor.decode(image_text_tensors[0], skip_special_tokens=True)
+    return output
+
+gr.close_all()
+
+app = gr.Interface(fn=captioning,
+                   inputs=[gr.Image(label="Laita tähä joku kuva", type="pil")],
+                   outputs=[gr.Textbox(label="Mitä näkyy?")],
+                   title="Harzan kuvan selitys aplikaatio",
+                   description="Harzan ihme aplikaatio kertomaan mitä kuvassa on",
+                   allow_flagging="never")
+app.launch()
+gr.close_all()