updated port

.ipynb_checkpoints/app-checkpoint.py

@@ -0,0 +1,25 @@
+from fastapi import FastAPI, File, UploadFile
+from PIL import Image
+from transformers import AutoProcessor, Blip2ForConditionalGeneration
+import torch
+import io
+
+app = FastAPI()
+
+# Load the model and processor
+model = Blip2ForConditionalGeneration.from_pretrained("ybelkada/blip2-opt-2.7b-fp16-sharded")
+model.load_adapter('blip-cpu-model')
+processor = AutoProcessor.from_pretrained("Salesforce/blip2-opt-2.7b")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+@app.post("/generate-caption/")
+async def generate_caption(file: UploadFile = File(...)):
+    image = Image.open(io.BytesIO(await file.read()))
+    inputs = processor(images=image, return_tensors="pt").to(device, torch.float16)
+    
+    with torch.no_grad():
+        caption_ids = model.generate(**inputs, max_length=128)
+        caption = processor.decode(caption_ids[0], skip_special_tokens=True)
+    
+    return {"caption": caption}

.ipynb_checkpoints/start-checkpoint.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+
+# Start FastAPI
+uvicorn app:app --host 0.0.0.0 --port 8502 &
+
+# Start Streamlit
+streamlit run streamlit_app.py --server.port=8501 --server.address=0.0.0.0

.ipynb_checkpoints/streamlit_app-checkpoint.py

@@ -0,0 +1,18 @@
+import streamlit as st
+import requests
+from PIL import Image
+
+st.title("Image Captioning with Fine-Tuned BLiPv2 Model")
+
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    
+    files = {"file": uploaded_file.getvalue()}
+    response = requests.post("http://localhost:8502/generate-caption/", files=files)
+    caption = response.json().get("caption")
+    
+    st.write("Generated Caption:")
+    st.write(f"**{caption}**")

start.sh

@@ -1,7 +1,7 @@
 #!/bin/bash
 
 # Start FastAPI
-uvicorn app:app --host 0.0.0.0 --port 8501 &
+uvicorn app:app --host 0.0.0.0 --port 8502 &
 
 # Start Streamlit
-streamlit run streamlit_app.py --server.port=8502 --server.address=0.0.0.0
+streamlit run streamlit_app.py --server.port=8501 --server.address=0.0.0.0

streamlit_app.py

@@ -11,7 +11,7 @@ if uploaded_file is not None:
     st.image(image, caption="Uploaded Image", use_column_width=True)
     
     files = {"file": uploaded_file.getvalue()}
-    response = requests.post("http://localhost:8501/generate-caption/", files=files)
+    response = requests.post("http://localhost:8502/generate-caption/", files=files)
     caption = response.json().get("caption")
     
     st.write("Generated Caption:")