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app.py

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+import streamlit as st
+import cv2
+import numpy as np
+import os
+import tempfile
+from PIL import Image
+from ultralytics import YOLO
+import easyocr
+import re
+
+# ----------- Page config ----------------
+st.set_page_config(
+    page_title='Number plate',
+    page_icon='',
+    layout='wide'
+)
+
+
+
+st.title("Number plate")
+st.write('Upload an image or video to detect helmet')
+
+# -------------- load model detection -----------
+@st.cache_resource
+def load_model():
+    return YOLO('best.pt')
+
+@st.cache_resource
+def load_ocr():
+    return easyocr.Reader(['en'])
+
+model = load_model()
+ocr_model = load_ocr()
+
+
+
+# switching tabs
+x,y = st.tabs(['Image Detection','Video Detection'])
+
+# Tabs 1 == Image detection
+with x:
+    st.header('Image Detection')
+
+    img_path = st.file_uploader('Please upload an image') # upload option
+
+    if img_path is not None:
+        image = Image.open(img_path)
+        image_np = np.array(image) # converting in to atrray
+
+        # YOLO inference
+        result = model(image_np,conf=0.4)
+        annot_img = result[0].plot()
+
+        # Convert BGR to RGB
+        annot_img = cv2.cvtColor(annot_img, cv2.COLOR_BGR2RGB)
+
+        # --------------------- number detection ----------------------
+        detect_number = []
+
+        for box in result[0].boxes:
+            x1,y1,x2,y2 = map(int,box.xyxy[0])
+
+            plate_crop = image_np[y1:y2,x1:x2]
+            gray = cv2.cvtColor(plate_crop,cv2.COLOR_BGR2GRAY)
+
+            ocr_result = ocr_model.readtext(gray)
+
+
+            text = ""
+            for t in ocr_result:
+                text += t[1] + " "
+
+            plate_text = re.sub(r'[^A-Z0-9]', '', text.upper())
+
+            if plate_text:
+                detect_number.append(plate_text)
+
+
+
+        #st.subheader("Detected Result")
+        #st.image(annot_img, use_container_width=True)
+        #st.image(annot_img,width=400) # first image
+        #st.image(image,width=400) # last image
+
+        # to display side by side
+        ori_img,pre_img = st.columns(2)
+        with ori_img: # original image
+            st.markdown('#### ***Original Image***')
+            st.image(image,width=500)
+
+        with pre_img:
+            st.markdown('#### ***Detected Image***')
+            st.image(annot_img,width=500)
+
+        # Display OCR text
+        if detect_number:
+            st.subheader("Detected Number Plate Text")
+            for num in detect_number:
+                st.success(num)
+        else:
+            st.warning("No number plate text detected")
+
+
+
+#------------------------------------------------------------------------
+# ----------       For Video detection         -------------------------
+#------------------------------------------------------------------------
+# ----------       For Video detection         -------------------------
+with y:
+    st.header("Video Number Plate Detection")
+
+    video_file = st.file_uploader(
+        "Upload a Video",
+        type=["mp4", "avi", "mov"]
+    )
+
+    if video_file is not None:
+        temp_video = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
+        temp_video.write(video_file.read())
+        temp_video.close()
+
+        cap = cv2.VideoCapture(temp_video.name)
+        stframe = st.empty()
+
+        while cap.isOpened():
+            ret, frame = cap.read()
+            if not ret:
+                break
+
+            # YOLO inference
+            results = model(frame, conf=0.4)
+            annotated_frame = frame.copy()
+
+            for box in results[0].boxes:
+                x1, y1, x2, y2 = map(int, box.xyxy[0])
+
+                plate_crop = frame[y1:y2, x1:x2]
+                if plate_crop.size == 0:
+                    continue
+
+                gray = cv2.cvtColor(plate_crop, cv2.COLOR_BGR2GRAY)
+
+                # OCR
+                ocr_result = ocr_model.readtext(gray)
+                text = " ".join([t[1] for t in ocr_result])
+                plate_text = re.sub(r'[^A-Z0-9]', '', text.upper())
+
+                # Draw bounding box
+                cv2.rectangle(
+                    annotated_frame,
+                    (x1, y1),
+                    (x2, y2),
+                    (0, 255, 0),
+                    2
+                )
+
+                # Draw plate text
+                if plate_text:
+                    cv2.putText(
+                        annotated_frame,
+                        plate_text,
+                        (x1, y1 - 10),
+                        cv2.FONT_HERSHEY_SIMPLEX,
+                        0.8,
+                        (0, 255, 0),
+                        2
+                    )
+
+            stframe.image(annotated_frame, channels="BGR", width=800)
+
+        cap.release()
+        os.remove(temp_video.name)
+        st.success("Video processing completed")
+
+
+                                        
+
+
+
+
+
+
+st.markdown("""
+<br>
+<div style='text-align:center; padding:12px; background-color:#111111; border-radius:10px;'>
+<span style='color:#AAAAAA; font-size:16px;'>
+Designed & Developed by <b style='color:#CCCCCC;'>Yedeedya Injeti</b><br>
+Under <b style='color:#B8860B;'>Innomatics Research Labs</b>
+</span>
+</div>
+<br>
+""", unsafe_allow_html=True)
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best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:71a1ab4efc46650a51a8f878e39c5c166f3915542d3f1a90774e7766c14deb48
+size 22514922

requirements.txt

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+altair==6.0.0
+attrs==25.4.0
+blinker==1.9.0
+cachetools==6.2.6
+certifi==2026.1.4
+charset-normalizer==3.4.4
+click==8.3.1
+colorama==0.4.6
+contourpy==1.3.2
+cycler==0.12.1
+easyocr==1.7.2
+filelock==3.20.3
+fonttools==4.61.1
+fsspec==2026.1.0
+gitdb==4.0.12
+GitPython==3.1.46
+idna==3.11
+ImageIO==2.37.2
+Jinja2==3.1.6
+jsonschema==4.26.0
+jsonschema-specifications==2025.9.1
+kiwisolver==1.4.9
+lazy_loader==0.4
+MarkupSafe==3.0.3
+matplotlib==3.10.8
+mpmath==1.3.0
+narwhals==2.15.0
+networkx==3.4.2
+ninja==1.13.0
+numpy==2.2.6
+opencv-python==4.13.0.90
+opencv-python-headless==4.13.0.90
+packaging==26.0
+pandas==2.3.3
+pi==0.1.2
+pillow==12.1.0
+polars==1.37.1
+polars-runtime-32==1.37.1
+protobuf==6.33.4
+psutil==7.2.1
+pyarrow==23.0.0
+pyclipper==1.4.0
+pydeck==0.9.1
+pyparsing==3.3.2
+python-bidi==0.6.7
+python-dateutil==2.9.0.post0
+pytz==2025.2
+PyYAML==6.0.3
+referencing==0.37.0
+requests==2.32.5
+rpds-py==0.30.0
+scikit-image==0.25.2
+scipy==1.15.3
+shapely==2.1.2
+six==1.17.0
+smmap==5.0.2
+streamlit==1.53.1
+sympy==1.14.0
+tenacity==9.1.2
+tifffile==2025.5.10
+toml==0.10.2
+torch==2.9.1
+torchvision==0.24.1
+tornado==6.5.4
+typing_extensions==4.15.0
+tzdata==2025.3
+ultralytics==8.4.8
+ultralytics-thop==2.0.18
+urllib3==2.6.3
+watchdog==6.0.0

yolo26n.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9b09cc8bf347f0fc8a5f7657480587f25db09b34bf33b0652110fb03a8ad4fef
+size 5544453