Update app.py

app.py

@@ -17,34 +17,6 @@ st.write("Upload an invoice image to extract the table (code article, designatio
 
 uploaded_file = st.file_uploader("Choose an image", type=["png", "jpg", "jpeg"])
 
-if uploaded_file is not None:
-    image = Image.open(uploaded_file).convert("RGB")
-    st.image(image, caption="Uploaded Invoice", use_column_width=True)
-
-    with st.spinner("🔍 Analyzing..."):
-        # Preprocess image
-        pixel_values = processor(image, return_tensors="pt").pixel_values
-
-        # Prompt for table extraction
-        import streamlit as st
-from PIL import Image
-from transformers import DonutProcessor, VisionEncoderDecoderModel
-import torch
-
-# Load Donut model and processor
-@st.cache_resource
-def load_model():
-    processor = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-docvqa")
-    model = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-docvqa")
-    return processor, model
-
-processor, model = load_model()
-
-st.title("🧾 Invoice Table Extractor - Hugging Face Donut")
-st.write("Upload an invoice image to extract the table (code article, designation, quantity, unit prices, totals).")
-
-uploaded_file = st.file_uploader("Choose an image", type=["png", "jpg", "jpeg"])
-
 if uploaded_file is not None:
     image = Image.open(uploaded_file).convert("RGB")
     st.image(image, caption="Uploaded Invoice", use_column_width=True)
@@ -71,21 +43,6 @@ if uploaded_file is not None:
 
     st.subheader("📋 Extracted Table Info")
     st.code(result)
-        decoder_input_ids = processor.tokenizer(prompt, add_special_tokens=False, return_tensors="pt").input_ids
 
-        # Generate prediction
-        outputs = model.generate(
-            pixel_values,
-            decoder_input_ids=decoder_input_ids,
-            max_length=512,
-            early_stopping=True
-        )
-
-        # Decode response
-        result = processor.batch_decode(outputs, skip_special_tokens=True)[0]
-        result = result.replace("<s_docvqa><question>", "").replace("</question><answer>", "").strip()
-
-    st.subheader("📋 Extracted Table Info")
-    st.code(result)