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add snapshots & counter

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raven
2026-01-12 21:59:59 -03:00
parent de399fe3f8
commit 24b04f84ab
4 changed files with 92 additions and 25 deletions
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78
alpr-service/main.py
View File

@@ -5,16 +5,18 @@ import os
import time
import threading
import re
from datetime import datetime
from queue import Queue
from flask import Flask, Response
from flask import Flask, Response, jsonify
from flask_cors import CORS
from ultralytics import YOLO
# Configuration
BACKEND_URL = os.environ.get('BACKEND_URL', 'http://localhost:3000')
CAMERA_ID = 0
PROCESS_INTERVAL = 1.5 # Más reactivo
PROCESS_INTERVAL = 1.5
MODEL_PATH = 'best.pt'
DATASET_DIR = '/app/dataset' # Carpeta para guardar capturas
app = Flask(__name__)
CORS(app)
@@ -25,9 +27,32 @@ frame_lock = threading.Lock()
latest_detections = []
detection_lock = threading.Lock()
# Cola para procesamiento OCR asíncrono
# Cola para procesamiento OCR asíncrono (ahora incluye frame completo)
ocr_queue = Queue(maxsize=5)
# Crear carpeta de dataset si no existe
os.makedirs(DATASET_DIR, exist_ok=True)
print(f"📁 Dataset directory: {DATASET_DIR}")
def save_plate_capture(plate_number, plate_img, full_frame):
"""Guarda la captura de la patente para el dataset"""
try:
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
# Guardar imagen recortada de la patente
plate_filename = f"{DATASET_DIR}/{plate_number}_{timestamp}_plate.jpg"
cv2.imwrite(plate_filename, plate_img, [cv2.IMWRITE_JPEG_QUALITY, 95])
# Guardar frame completo con contexto
frame_filename = f"{DATASET_DIR}/{plate_number}_{timestamp}_full.jpg"
cv2.imwrite(frame_filename, full_frame, [cv2.IMWRITE_JPEG_QUALITY, 90])
print(f"📸 Saved to dataset: {plate_number}")
return True
except Exception as e:
print(f"❌ Error saving capture: {e}")
return False
def send_plate(plate_number):
"""Envía la patente detectada al backend"""
try:
@@ -37,22 +62,21 @@ def send_plate(plate_number):
except Exception as e:
print(f"✗ Error sending plate: {e}")
def validate_and_send(text):
"""Valida formato chileno y envía"""
def validate_plate(text):
"""Valida formato chileno"""
# Formato nuevo: XXXX-00 | Formato antiguo: XX-0000
if re.match(r'^[A-Z]{4}\d{2}$', text) or re.match(r'^[A-Z]{2}\d{4}$', text):
send_plate(text)
return True
return False
return bool(re.match(r'^[A-Z]{4}\d{2}$', text) or re.match(r'^[A-Z]{2}\d{4}$', text))
def ocr_worker(reader):
"""Hilo dedicado para OCR - no bloquea el stream"""
while True:
try:
plate_img = ocr_queue.get(timeout=1)
if plate_img is None:
data = ocr_queue.get(timeout=1)
if data is None:
continue
plate_img, full_frame = data
# Preprocesamiento para mejor OCR
gray = cv2.cvtColor(plate_img, cv2.COLOR_BGR2GRAY)
@@ -60,8 +84,11 @@ def ocr_worker(reader):
allowlist='ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789')
for text in ocr_results:
clean_text = ''.join(e for e in text if e.isalnum()).upper()
if len(clean_text) >= 6:
validate_and_send(clean_text)
if len(clean_text) >= 6 and validate_plate(clean_text):
# Enviar al backend
send_plate(clean_text)
# Guardar captura para dataset
save_plate_capture(clean_text, plate_img, full_frame)
except:
pass
@@ -96,10 +123,9 @@ def camera_loop():
print("✅ System ready!")
last_process_time = 0
frame_count = 0
while True:
# Captura eficiente - solo 2 grabs
# Captura eficiente
cap.grab()
cap.grab()
ret, frame = cap.retrieve()
@@ -108,14 +134,13 @@ def camera_loop():
time.sleep(0.01)
continue
frame_count += 1
current_time = time.time()
# Procesar ALPR cada PROCESS_INTERVAL segundos
if current_time - last_process_time > PROCESS_INTERVAL:
last_process_time = current_time
# YOLO detection - usar imgsz pequeño para velocidad
# YOLO detection
results = model(frame, verbose=False, imgsz=320, conf=0.5)
new_detections = []
@@ -125,15 +150,16 @@ def camera_loop():
conf = float(box.conf[0])
new_detections.append((x1, y1, x2, y2, conf))
# Extraer imagen de placa y enviar a cola OCR
# Extraer imagen de placa
plate_img = frame[y1:y2, x1:x2].copy()
if plate_img.size > 0 and not ocr_queue.full():
ocr_queue.put(plate_img)
# Enviar placa Y frame completo para dataset
ocr_queue.put((plate_img, frame.copy()))
with detection_lock:
latest_detections = new_detections
# Actualizar frame para streaming (sin bloquear)
# Actualizar frame para streaming
display_frame = frame
with detection_lock:
for (x1, y1, x2, y2, conf) in latest_detections:
@@ -148,7 +174,7 @@ def generate():
"""Generador para streaming MJPEG"""
global outputFrame
while True:
time.sleep(0.033) # ~30 FPS para el stream
time.sleep(0.033)
with frame_lock:
if outputFrame is None:
continue
@@ -163,6 +189,16 @@ def video_feed():
def health():
return {"status": "ok", "service": "alpr"}
@app.route("/dataset/count")
def dataset_count():
"""Endpoint para ver cuántas capturas hay en el dataset"""
try:
files = os.listdir(DATASET_DIR)
plates = len([f for f in files if f.endswith('_plate.jpg')])
return {"plates_captured": plates, "total_files": len(files)}
except:
return {"plates_captured": 0, "total_files": 0}
if __name__ == "__main__":
t = threading.Thread(target=camera_loop, daemon=True)
t.start()

2
docker-compose.yml
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@@ -60,6 +60,8 @@ services:
- backend
restart: unless-stopped
privileged: true
volumes:
- ./alpr-service/dataset:/app/dataset
# Frontend Service (React)
frontend:

33
frontend/src/pages/AdminDashboard.jsx
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@@ -1,7 +1,7 @@
import { useState, useEffect } from 'react';
import axios from 'axios';
import io from 'socket.io-client';
import { Users, CheckCircle, XCircle, Shield, Trash2, Camera, AlertCircle } from 'lucide-react';
import { Users, CheckCircle, XCircle, Shield, Trash2, Camera, AlertCircle, Database } from 'lucide-react';
import { useTranslation } from 'react-i18next';
import LanguageSelector from '../components/LanguageSelector';
@@ -26,8 +26,15 @@ function AdminDashboard({ token }) {
const [searchRut, setSearchRut] = useState('');
const [searchResult, setSearchResult] = useState(null); // null | { found: true, data: ... } | { found: false }
// Dataset State
const [datasetCount, setDatasetCount] = useState(0);
useEffect(() => {
fetchData();
fetchDatasetCount();
// Actualizar contador de dataset cada 10 segundos
const datasetInterval = setInterval(fetchDatasetCount, 10000);
// Live detection listener
socket.on('new_detection', (data) => {
@@ -48,6 +55,7 @@ function AdminDashboard({ token }) {
socket.off('plate_status_updated');
socket.off('plate_deleted');
socket.off('person_deleted');
clearInterval(datasetInterval);
};
}, [token]);
@@ -88,6 +96,15 @@ function AdminDashboard({ token }) {
}
};
const fetchDatasetCount = async () => {
try {
const res = await axios.get('/dataset/count');
setDatasetCount(res.data.plates_captured || 0);
} catch (err) {
console.log('Dataset count not available');
}
};
const handleSearchRut = (e) => {
e.preventDefault();
const normalizedRut = searchRut.replace(/\./g, '').toUpperCase();
@@ -201,9 +218,17 @@ function AdminDashboard({ token }) {
<h2 className="text-xl font-bold flex items-center gap-2">
<Camera /> {t('monitor_area')}
</h2>
<div className="flex bg-slate-800 rounded p-1">
<button onClick={() => setViewMode('live')} className={`px-3 py-1 rounded ${viewMode === 'live' ? 'bg-blue-600' : ''}`}>Live</button>
<button onClick={() => setViewMode('history')} className={`px-3 py-1 rounded ${viewMode === 'history' ? 'bg-blue-600' : ''}`}>History</button>
<div className="flex items-center gap-4">
{/* Dataset Counter */}
<div className="flex items-center gap-2 bg-gradient-to-r from-emerald-900/50 to-teal-900/50 px-4 py-2 rounded-lg border border-emerald-700/50">
<Database size={18} className="text-emerald-400" />
<span className="text-emerald-300 font-mono font-bold">{datasetCount}</span>
<span className="text-emerald-400/70 text-sm">capturas</span>
</div>
<div className="flex bg-slate-800 rounded p-1">
<button onClick={() => setViewMode('live')} className={`px-3 py-1 rounded ${viewMode === 'live' ? 'bg-blue-600' : ''}`}>Live</button>
<button onClick={() => setViewMode('history')} className={`px-3 py-1 rounded ${viewMode === 'history' ? 'bg-blue-600' : ''}`}>History</button>
</div>
</div>
</div>

4
frontend/vite.config.js
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@@ -18,6 +18,10 @@ export default defineConfig({
'/video_feed': {
target: 'http://alpr-service:5001',
changeOrigin: true
},
'/dataset': {
target: 'http://alpr-service:5001',
changeOrigin: true
}
}
}