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8d960ee | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | # YFCC50K Photo Corpus Scripts
Pipeline for curating, fetching, and uploading the Lightcella photo corpus
from the YFCC100M dataset.
## Pipeline
### Step 1: Curate (`curate_manifest.py`)
Selects 50k photos from YFCC100M with date/GPS/resolution stratification.
Requires:
- YFCC100M SQLite database (~65GB): `yfcc100m_dataset.sql`
- MediaEval placing subset files (downloaded automatically via AWS CLI)
- Python packages: `yfcc100m`, `opencv-python-headless`, `awscli`
Three phases run sequentially:
1. **Build metadata** -- scans YFCC SQLite for MediaEval placing hashes, extracts GPS/date/Flickr credentials
2. **Select subset** -- stratified sampling by date, GPS, faces, resolution tiers
3. **Upgrade resolution** -- probes Flickr for higher-res versions, assigns fetch tiers
```bash
python curate_manifest.py --db /path/to/yfcc100m_dataset.sql --out-dir ./output
```
Output: `manifest.tsv` (the same format shipped in this repo).
### Step 2: Fetch (`fetch_flickr.py`)
Downloads Flickr originals for manifest entries. Resumable, rate-limit aware.
```bash
python fetch_flickr.py --manifest manifest.tsv --out-dir ./photos
```
Features:
- Classifies Flickr users as alive/dead/unsampled for efficient probing
- Validates JPEG dimensions (skips <501px max edge)
- Restores file mtime from manifest date (fallback for EXIF-less photos)
- Automatic retry with backoff on 429s
### Step 3: Upload (`upload_hf.py`)
Creates ~1GB tar shards and uploads them to HuggingFace.
```bash
python upload_hf.py --src-dir ./photos --repo lightcella/photo-corpus --prefix yfcc
```
Features:
- Resumable (skips already-uploaded shards)
- Deletes local tar after successful upload to save disk
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