init

app.py

@@ -0,0 +1,36 @@
+from transformers import  BlipForConditionalGeneration
+from transformers import AutoProcessor
+from PIL import Image
+import requests
+import gradio as gr
+
+url = "http://images.cocodataset.org/val2017/000000039769.jpg"
+image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
+
+
+processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+
+
+image = processor(image, return_tensors="pt")
+generated_ids = model.generate(**image)
+generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
+print(generated_text)
+
+
+
+def launch(input):
+    url = input
+    image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
+    processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+    model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
+    image = processor(image, return_tensors="pt")
+    generated_ids = model.generate(**image)
+    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0].strip()
+    return generated_text
+  
+  
+iface = gr.Interface(fn=launch, inputs="text", outputs="text")
+  
+iface.launch()
+