Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,28 +1,32 @@
-import streamlit as st
+import os
+os.environ['PADDLEX_HOME'] = '/tmp/.paddlex'  # Fix for Hugging Face permission error
+
 from paddleocr import PaddleOCR
 from PIL import Image
+import streamlit as st
 import numpy as np
 import re
 
-# Initialize OCR
-ocr = PaddleOCR(use_angle_cls=True, lang='en')
+# Initialize PaddleOCR model
+ocr = PaddleOCR(use_angle_cls=True, lang='en')  # Enable angle classification
 
+# Streamlit page setup
 st.set_page_config(page_title="Auto Weight Logger", layout="centered")
 st.title("📷 Auto Weight Logger")
 
-# Upload image
+# File uploader
 uploaded_file = st.file_uploader("Upload an image of the weight display", type=["jpg", "jpeg", "png"])
 
 if uploaded_file is not None:
-    # Load image using PIL (no OpenCV)
+    # Display uploaded image
     image = Image.open(uploaded_file).convert("RGB")
     st.image(image, caption="Uploaded Image", use_column_width=True)
 
-    # Convert PIL image to numpy array
+    # Convert image to numpy array for OCR
     img_array = np.array(image)
 
-    # Run OCR
-    with st.spinner("Detecting weight..."):
+    # OCR Detection
+    with st.spinner("🔍 Detecting weight..."):
         result = ocr.ocr(img_array, cls=True)
 
         weight = "Not detected"
@@ -36,5 +40,7 @@ if uploaded_file is not None:
                     weight = match.group()
                     confidence = conf
                     break
+            if weight != "Not detected":
+                break
 
         st.markdown(f"### ✅ Weight: **{weight} kg** (Confidence: {confidence:.2%})")