Update app.py

app.py

@@ -17,6 +17,34 @@ 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)
@@ -43,5 +71,21 @@ 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)