| --- |
| title: Project Halide |
| emoji: "\U0001F525" |
| colorFrom: orange |
| colorTo: red |
| sdk: gradio |
| sdk_version: 6.16.0 |
| app_file: app.py |
| pinned: false |
| license: apache-2.0 |
| short_description: Edge-native diagnostic engine for analog film scans |
| --- |
| |
| # Project Halide |
|
|
| An edge-native diagnostic engine for analog film. Upload a film scan, fill in |
| film stock + storage metadata, and Project Halide runs a two-stage analysis: |
|
|
| 1. **Vision Extraction** -- MiniCPM-V 4.6 (1.3B params, fine-tuned with LoRA on |
| the FilmDamageSimulator dataset) detects dust, dirt, scratches, and hair |
| artifacts as normalized bounding boxes. |
| 2. **Diagnostic Reasoning** -- Nemotron-Mini-4B-Instruct (4B params) with |
| 3-shot prompting cross-references the defect report against your film stock |
| and storage metadata, and prescribes specific physical fixes a lab can |
| perform. |
|
|
| The full pipeline runs locally in the Space. No external APIs. Models are |
| loaded from a private Hugging Face repo at startup. |
|
|
| ## How to use |
|
|
| 1. Upload a film scan (PNG or JPEG, ideally 35mm or 120 frame). |
| 2. Select your film stock from the dropdown. |
| 3. Adjust the age and storage condition. |
| 4. Pick the scan resolution you used. |
| 5. Click **Diagnose scan**. |
|
|
| Results are stored in a local SQLite database. The "Recent diagnoses" panel |
| shows the last 10 runs in this Space session. |
|
|
| ## Models |
|
|
| - Vision: `Lonelyguyse1/halide-vision` (private), based on |
| `openbmb/MiniCPM-V-4_6`. |
| - Reasoning: `nvidia/Nemotron-Mini-4B-Instruct` (public, 4B params, few-shot |
| prompting only, no fine-tuning). |
|
|
| ## License |
|
|
| Apache 2.0. |
|
|
