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| title: Car Analysis Advisor (Multi‑Image, Deterministic) | |
| emoji: 🛠️ | |
| colorFrom: purple | |
| colorTo: indigo | |
| sdk: gradio | |
| sdk_version: "4.36.1" | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| tags: | |
| - automotive | |
| - computer-vision | |
| - service-advisor | |
| - gradio | |
| # Car Analysis Advisor (Hugging Face Space) | |
| An end‑to‑end **car analysis AI** that ingests **multiple images** of a vehicle and outputs **precise, actionable recommendations**: | |
| - **Model** (zero‑shot CLIP baseline; optional fine‑tune) | |
| - **Color** (dominant body color with named snapping) | |
| - **Issues** (mechanical/aesthetic) → **deterministic** final decisions | |
| - **Exact price estimate** (parts + labor + region multipliers) | |
| - **PDF & JSON** export | |
| No probability scores are exposed—only clear decisions & totals. | |
| ## Run locally | |
| ```bash | |
| pip install -r requirements.txt | |
| python app.py | |
| ``` | |
| ## Train (optional, improves accuracy) | |
| See `training/train_classifier.py` for a ViT fine‑tuning script. | |
| Dataset CSV: | |
| ```csv | |
| image_path,label | |
| images/nexon_001.jpg,Tata Nexon | |
| ``` | |
| Then: | |
| ```bash | |
| python training/train_classifier.py --data_root data/your_dataset --annotations data/your_dataset/annotations.csv --out_dir checkpoints/vision | |
| ``` | |
| ## Pricing configuration | |
| - `configs/parts_catalog.yaml` — parts & standard labor hours per issue | |
| - `configs/regions.yaml` — labor rates & part multipliers per region (example values provided) | |
| ## Deterministic decisions | |
| Internally, scores are computed but **final outputs are rule‑based** (top evidence & thresholds) to provide **unambiguous** issue lists and **exact** costs. | |
| ## Exports | |
| - `exports/report.pdf` | |
| - `exports/report.json` | |