Files
vehicle-counter/app.py
Joachim Hummel 504f8c0b69 Implementiere Fahrzeugzählung mit Linienüberquerung
- Linienschnitt-Algorithmus für präzise Fahrzeugzählung
- Interaktive Linienauswahl im Browser (Canvas-basiert)
- Session-Management für benutzerdefinierte Zähllinien
- Typ-spezifische Zähler (Autos, LKW, Busse, Motorräder)
- REST-API für Linienkonfiguration und Zähler-Reset
- Gestrichelte Zähllinie als Video-Overlay
- Detailliertes Zähler-Display im Video

Features:
- Linienüberquerung-Erkennung (beide Richtungen)
- Keine Mehrfachzählung durch Track-ID-Management
- Funktioniert für Webcam und Video-Upload
- Benutzerfreundliche UI mit Echtzeit-Feedback

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2025-12-08 14:42:46 +00:00

304 lines
13 KiB
Python

import os
import cv2
import numpy as np
from flask import Flask, render_template, Response, request, redirect, url_for, send_from_directory, session, jsonify
from ultralytics import YOLO
app = Flask(__name__)
app.secret_key = 'vehicle_counting_secret_key_2024' # Required for session management
# Load the YOLOv8 model
model = YOLO("yolo11s.pt")
names = model.model.names
# Vehicle classes to count
VEHICLE_CLASSES = {'car', 'truck', 'bus', 'motorcycle'}
# Helper function to check if two line segments intersect
def line_intersect(p1, p2, p3, p4):
"""
Check if line segment p1-p2 intersects with line segment p3-p4
Returns True if they intersect, False otherwise
"""
x1, y1 = p1
x2, y2 = p2
x3, y3 = p3
x4, y4 = p4
denom = (x1 - x2) * (y3 - y4) - (y1 - y2) * (x3 - x4)
if abs(denom) < 1e-10:
return False
t = ((x1 - x3) * (y3 - y4) - (y1 - y3) * (x3 - x4)) / denom
u = -((x1 - x2) * (y1 - y3) - (y1 - y2) * (x1 - x3)) / denom
return 0 <= t <= 1 and 0 <= u <= 1
@app.route('/')
def index():
return render_template('index.html')
@app.route('/start_webcam')
def start_webcam():
# Initialize default counting line in session if not set
if 'counting_line' not in session:
session['counting_line'] = {'x1': 0, 'y1': 300, 'x2': 1020, 'y2': 300}
return render_template('webcam.html')
@app.route('/api/set_line', methods=['POST'])
def set_counting_line():
"""API endpoint to set the counting line coordinates"""
data = request.json
session['counting_line'] = {
'x1': int(data['x1']),
'y1': int(data['y1']),
'x2': int(data['x2']),
'y2': int(data['y2'])
}
return jsonify({'status': 'success', 'line': session['counting_line']})
@app.route('/api/get_line', methods=['GET'])
def get_counting_line():
"""API endpoint to get the current counting line coordinates"""
if 'counting_line' not in session:
session['counting_line'] = {'x1': 0, 'y1': 300, 'x2': 1020, 'y2': 300}
return jsonify(session['counting_line'])
@app.route('/api/reset_count', methods=['POST'])
def reset_count():
"""API endpoint to reset the vehicle count"""
session['reset_count'] = True
return jsonify({'status': 'success'})
def detect_objects_from_webcam():
count = 0
cap = cv2.VideoCapture(0) # 0 for the default webcam
# Track vehicle positions and counted IDs
track_positions = {} # {track_id: (center_x, center_y)}
counted_ids = set()
vehicle_count = 0
vehicle_type_counts = {'car': 0, 'truck': 0, 'bus': 0, 'motorcycle': 0}
while True:
ret, frame = cap.read()
if not ret:
break
count += 1
if count % 2 != 0:
continue
# Resize the frame to (1020, 600)
frame = cv2.resize(frame, (1020, 600))
# Get counting line from session (default to horizontal middle line)
line_data = session.get('counting_line', {'x1': 0, 'y1': 300, 'x2': 1020, 'y2': 300})
line_start = (line_data['x1'], line_data['y1'])
line_end = (line_data['x2'], line_data['y2'])
# Check if count should be reset
if session.get('reset_count', False):
counted_ids.clear()
vehicle_count = 0
vehicle_type_counts = {'car': 0, 'truck': 0, 'bus': 0, 'motorcycle': 0}
session['reset_count'] = False
# Draw counting line (dashed yellow line with black gaps)
cv2.line(frame, line_start, line_end, (0, 255, 255), 2, cv2.LINE_AA)
# Draw dashed effect
line_length = int(np.sqrt((line_end[0] - line_start[0])**2 + (line_end[1] - line_start[1])**2))
dash_length = 20
for i in range(0, line_length, dash_length * 2):
t1 = i / line_length
t2 = min((i + dash_length) / line_length, 1.0)
x1 = int(line_start[0] + t1 * (line_end[0] - line_start[0]))
y1 = int(line_start[1] + t1 * (line_end[1] - line_start[1]))
x2 = int(line_start[0] + t2 * (line_end[0] - line_start[0]))
y2 = int(line_start[1] + t2 * (line_end[1] - line_start[1]))
cv2.line(frame, (x1, y1), (x2, y2), (0, 0, 0), 2)
# Run YOLOv8 tracking on the frame
results = model.track(frame, persist=True)
if results[0].boxes is not None and results[0].boxes.id is not None:
boxes = results[0].boxes.xyxy.int().cpu().tolist()
class_ids = results[0].boxes.cls.int().cpu().tolist()
track_ids = results[0].boxes.id.int().cpu().tolist()
for box, class_id, track_id in zip(boxes, class_ids, track_ids):
c = names[class_id]
x1, y1, x2, y2 = box
# Calculate center point of bounding box
center_x = (x1 + x2) // 2
center_y = (y1 + y2) // 2
# Check if this is a vehicle we want to count
if c in VEHICLE_CLASSES:
# If we have a previous position for this track
if track_id in track_positions and track_id not in counted_ids:
prev_x, prev_y = track_positions[track_id]
# Check if the vehicle crossed the counting line
if line_intersect((prev_x, prev_y), (center_x, center_y), line_start, line_end):
counted_ids.add(track_id)
vehicle_count += 1
vehicle_type_counts[c] += 1
# Update position
track_positions[track_id] = (center_x, center_y)
# Draw bounding box and label
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
cv2.putText(frame, f'{track_id} - {c}', (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 255), 1)
# Display vehicle count with type breakdown
cv2.rectangle(frame, (10, 10), (350, 140), (0, 0, 0), -1)
cv2.putText(frame, f'Gesamt: {vehicle_count}', (20, 35), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
cv2.putText(frame, f'Autos: {vehicle_type_counts["car"]}', (20, 65), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (200, 200, 200), 1)
cv2.putText(frame, f'LKW: {vehicle_type_counts["truck"]}', (20, 90), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (200, 200, 200), 1)
cv2.putText(frame, f'Busse: {vehicle_type_counts["bus"]}', (20, 115), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (200, 200, 200), 1)
cv2.putText(frame, f'Motorraeder: {vehicle_type_counts["motorcycle"]}', (20, 135), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (200, 200, 200), 1)
_, buffer = cv2.imencode('.jpg', frame)
frame = buffer.tobytes()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
@app.route('/webcam_feed')
def webcam_feed():
return Response(detect_objects_from_webcam(),
mimetype='multipart/x-mixed-replace; boundary=frame')
@app.route('/upload', methods=['POST'])
def upload_video():
if 'file' not in request.files:
return redirect(request.url)
file = request.files['file']
if file.filename == '':
return redirect(request.url)
# Save the uploaded file to the uploads folder
if not os.path.exists('uploads'):
os.makedirs('uploads')
file_path = os.path.join('uploads', file.filename)
file.save(file_path)
# Redirect to the video playback page after upload
return redirect(url_for('play_video', filename=file.filename))
@app.route('/uploads/<filename>')
def play_video(filename):
# Initialize default counting line in session if not set
if 'counting_line' not in session:
session['counting_line'] = {'x1': 0, 'y1': 300, 'x2': 1020, 'y2': 300}
return render_template('play_video.html', filename=filename)
@app.route('/video/<path:filename>')
def send_video(filename):
return send_from_directory('uploads', filename)
def detect_objects_from_video(video_path):
cap = cv2.VideoCapture(video_path)
count = 0
# Track vehicle positions and counted IDs
track_positions = {} # {track_id: (center_x, center_y)}
counted_ids = set()
vehicle_count = 0
vehicle_type_counts = {'car': 0, 'truck': 0, 'bus': 0, 'motorcycle': 0}
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
count += 1
if count % 2 != 0:
continue
# Resize the frame to (1020, 600)
frame = cv2.resize(frame, (1020, 600))
# Get counting line from session (default to horizontal middle line)
line_data = session.get('counting_line', {'x1': 0, 'y1': 300, 'x2': 1020, 'y2': 300})
line_start = (line_data['x1'], line_data['y1'])
line_end = (line_data['x2'], line_data['y2'])
# Check if count should be reset
if session.get('reset_count', False):
counted_ids.clear()
vehicle_count = 0
vehicle_type_counts = {'car': 0, 'truck': 0, 'bus': 0, 'motorcycle': 0}
session['reset_count'] = False
# Draw counting line (dashed yellow line with black gaps)
cv2.line(frame, line_start, line_end, (0, 255, 255), 2, cv2.LINE_AA)
# Draw dashed effect
line_length = int(np.sqrt((line_end[0] - line_start[0])**2 + (line_end[1] - line_start[1])**2))
dash_length = 20
for i in range(0, line_length, dash_length * 2):
t1 = i / line_length
t2 = min((i + dash_length) / line_length, 1.0)
x1 = int(line_start[0] + t1 * (line_end[0] - line_start[0]))
y1 = int(line_start[1] + t1 * (line_end[1] - line_start[1]))
x2 = int(line_start[0] + t2 * (line_end[0] - line_start[0]))
y2 = int(line_start[1] + t2 * (line_end[1] - line_start[1]))
cv2.line(frame, (x1, y1), (x2, y2), (0, 0, 0), 2)
# Run YOLOv8 tracking on the frame
results = model.track(frame, persist=True)
if results[0].boxes is not None and results[0].boxes.id is not None:
boxes = results[0].boxes.xyxy.int().cpu().tolist()
class_ids = results[0].boxes.cls.int().cpu().tolist()
track_ids = results[0].boxes.id.int().cpu().tolist()
for box, class_id, track_id in zip(boxes, class_ids, track_ids):
c = names[class_id]
x1, y1, x2, y2 = box
# Calculate center point of bounding box
center_x = (x1 + x2) // 2
center_y = (y1 + y2) // 2
# Check if this is a vehicle we want to count
if c in VEHICLE_CLASSES:
# If we have a previous position for this track
if track_id in track_positions and track_id not in counted_ids:
prev_x, prev_y = track_positions[track_id]
# Check if the vehicle crossed the counting line
if line_intersect((prev_x, prev_y), (center_x, center_y), line_start, line_end):
counted_ids.add(track_id)
vehicle_count += 1
vehicle_type_counts[c] += 1
# Update position
track_positions[track_id] = (center_x, center_y)
# Draw bounding box and label
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
cv2.putText(frame, f'{track_id} - {c}', (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 255), 1)
# Display vehicle count with type breakdown
cv2.rectangle(frame, (10, 10), (350, 140), (0, 0, 0), -1)
cv2.putText(frame, f'Gesamt: {vehicle_count}', (20, 35), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
cv2.putText(frame, f'Autos: {vehicle_type_counts["car"]}', (20, 65), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (200, 200, 200), 1)
cv2.putText(frame, f'LKW: {vehicle_type_counts["truck"]}', (20, 90), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (200, 200, 200), 1)
cv2.putText(frame, f'Busse: {vehicle_type_counts["bus"]}', (20, 115), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (200, 200, 200), 1)
cv2.putText(frame, f'Motorraeder: {vehicle_type_counts["motorcycle"]}', (20, 135), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (200, 200, 200), 1)
_, buffer = cv2.imencode('.jpg', frame)
frame = buffer.tobytes()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
@app.route('/video_feed/<filename>')
def video_feed(filename):
video_path = os.path.join('uploads', filename)
return Response(detect_objects_from_video(video_path),
mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == '__main__':
app.run('0.0.0.0',debug=False, port=8080)