Aboodtt404/CheKar

CarCheck Egypt — AI-powered used car inspection # CheKar — AI Car Inspection for Egypt CheKar uses AI to inspect used cars from photos. Take 8-12 photos of a car, get a graded report showing exterior condition, paint issues, accident signs, and repair cost estimates — all in Egyptian Arabic. ## How It Works 1. **Seller** photographs the car using the guided camera flow 2. **AI** analyzes photos with YOLO damage detection + Qwen vision model 3. **Report** shows a letter grade (A-F), traffic light status per category, and repair costs in EGP 4. **Buyer** knows what they're getting before seeing the car in person ## What It Assesses | Category | What It Checks | | ---------- | --------------- | | حالة الطلاء | Scratches, paint fading, repaint detection | | حالة الهيكل | Dents, structural deformation, panel gaps | | الزجاج والإضاءة | Cracked glass, broken headlights/taillights | | الداخلية | Seat wear, flood indicators, dashboard condition | | إشارات حوادث | Repaint patterns, panel misalignment, accident history | | المستندات | Odometer vs wear consistency, year/model verification | ## What It Cannot Assess (at the moment) - Engine, transmission, brakes, suspension — needs a mechanic - Electrical systems — needs diagnostic tools - Undercarriage — needs a lift - Odometer accuracy — not guaranteed from photos ## Tech Stack - **AI:** YOLO11 (damage detection) + Qwen3.5-27B-FP8 (vision analysis with cross-checking) - **Backend:** FastAPI + Huey (SQLite job queue) on a single VPS - **App:** Flutter (iOS + Android) - **Language:** Egyptian Arabic first, English secondary ## Project Structure ```text carcheck/ # Python backend — AI pipeline, API, scoring pipeline/ # YOLO + Qwen detection and analysis scoring/ # Letter grade + traffic light grading system api/ # FastAPI endpoints + Huey worker report/ # Arabic JSON + PDF report generation app/ # Flutter mobile app training/ # YOLO fine-tuning pipeline scripts/ # VPS setup and ser …