Add files using upload-large-folder tool

README.md

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+---
+pretty_name: bucketed-shards export
+license: other
+task_categories:
+  - text-to-image
+language:
+  - en
+tags:
+  - webdataset
+  - images
+  - captions
+---
+# A captioned and aspect ratio bucketed dataset of about 200k pexel photos with subjectively good aesthetic quality, with a diverse range of themes
+
+This version is scaled to approx 512^2 resolution.
+See below for more details
+
+## Bucketed Shards Dataset
+
+This repository contains a **bucketed-shards** export (uncompressed TAR shards).
+
+## Format
+
+- **Format**: `bucketed_shards_v1`
+- **Created**: `2026-01-08T09:51:12.478529+00:00`
+- **Export ID**: `export-2026-01-08T09:51:12.478529+00:00`
+- **Manifest**: `manifest.json`
+
+Directory layout:
+
+- `manifest.json` (global metadata + per-bucket shard listing)
+- `buckets/<bucket_id>/shard-*.tar`
+
+Each TAR shard contains 3 files per sample:
+
+- `<key>.jpg` (RGB JPEG)
+- `<key>.txt` (caption text, UTF-8, newline-terminated)
+- `<key>.json` (per-sample metadata: resize/crop/jpeg params + source size/path)
+
+## Image preprocessing
+
+All images are processed deterministically per-sample:
+
+- EXIF transpose, convert to RGB
+- **Cover-resize** using **torch CPU** bicubic interpolation with antialiasing (`mode=bicubic`, `antialias=True`)
+- **Never upsample**: samples that would require upscaling are skipped (`too_small_policy=drop`)
+- Crop to the bucket target size (`crop_strategy=corner`, allowed corners `[2, 3]`)
+
+Resize/crop details:
+
+- Cover scale is `scale = max(target_w / src_w, target_h / src_h)`; if `scale > 1`, the sample is skipped.
+- After resize, a crop box is chosen deterministically from the sample key (sha256 of `image_id`).
+  - Corner strategy chooses a corner from `allowed_corners` where `0=TL, 1=TR, 2=BL, 3=BR` (optional small jitter for `corner_jitter`).
+
+JPEG encoding:
+
+- quality `95`
+- subsampling policy `adaptive_scale` (adaptive threshold `0.85`)
+
+## Buckets / resolutions
+
+- Buckets follow **SDXL-style proto buckets** defined at a 1024×1024 base.
+- Base resolution(s): `[512]`
+- In single-res exports, `bucket_id` is the **proto** (1024-base) bucket, e.g. `p1024x1024`.
+- In multi-res exports, buckets are namespaced by base resolution: `r<base>_<proto>`, e.g. `r512_p1024x1024`.
+- The **actual target resolution** for each bucket (scaled by the per-bucket base resolution and `divisible=32`) is stored in:
+  - `manifest.json` → `buckets[<bucket_id>].scaled.w/h` (and `base_resolution`)
+  - each sample’s `<key>.json` → `base.w/h`, plus `resize` and `crop` details
+
+Bucket IDs (preview): `p1024x1024`, `p1024x960`, `p1088x896`, `p1088x960`, `p1152x832`, `p1152x896`, `p1216x832`, `p1280x768`, `p1344x704`, `p1344x768`, `p1408x704`, `p1472x704`, `p1536x640`, `p1600x640`, `p1664x576`, `p1728x576`, `p1792x576`, `p1856x512`, `p1984x512`, `p2048x512`, … (+13 more)
+
+Bucket distribution:
+
+| bucket_id | target_w×h | aspect | count |
+| --- | --- | --- | --- |
+| p832x1216 | 416×608 | 0.684 | 89,115 |
+| p1216x832 | 608×416 | 1.462 | 73,621 |
+| p832x1152 | 416×576 | 0.722 | 16,357 |
+| p896x1152 | 448×576 | 0.778 | 8,652 |
+| p1152x832 | 576×416 | 1.385 | 7,421 |
+| p1344x768 | 672×384 | 1.750 | 5,771 |
+| p768x1344 | 384×672 | 0.571 | 4,673 |
+| p1280x768 | 640×384 | 1.667 | 2,534 |
+| p1024x1024 | 512×512 | 1.000 | 1,912 |
+| p1152x896 | 576×448 | 1.286 | 1,647 |
+| p896x1088 | 448×544 | 0.824 | 1,485 |
+| p768x1280 | 384×640 | 0.600 | 1,244 |
+| p1344x704 | 672×352 | 1.909 | 402 |
+| p960x1088 | 480×544 | 0.882 | 388 |
+| p1088x896 | 544×448 | 1.214 | 381 |
+| p960x1024 | 480×512 | 0.938 | 300 |
+| p1024x960 | 512×480 | 1.067 | 246 |
+| p1088x960 | 544×480 | 1.133 | 236 |
+| p1408x704 | 704×352 | 2.000 | 145 |
+| p1472x704 | 736×352 | 2.091 | 133 |
+| p1536x640 | 768×320 | 2.400 | 69 |
+| p704x1408 | 352×704 | 0.500 | 69 |
+| p704x1472 | 352×736 | 0.478 | 35 |
+| p1600x640 | 800×320 | 2.500 | 34 |
+| p1664x576 | 832×288 | 2.889 | 25 |
+| p1728x576 | 864×288 | 3.000 | 19 |
+| p1792x576 | 896×288 | 3.111 | 15 |
+| p1856x512 | 928×256 | 3.625 | 8 |
+| p2048x512 | 1024×256 | 4.000 | 8 |
+| p640x1536 | 320×768 | 0.417 | 6 |
+| p1984x512 | 992×256 | 3.875 | 1 |
+| p512x2048 | 256×1024 | 0.250 | 1 |
+| p640x1600 | 320×800 | 0.400 | 1 |
+
+## Caption selection (waterfall)
+
+Captions are selected from `dataset.sqlite` using the first matching selector (highest priority wins).
+Within the same selector, the newest caption source is preferred.
+
+Caption provenance:
+
+- Per-sample `<key>.json` includes `caption_source_id` (int, from `dataset.sqlite`).
+- `manifest.json` includes a `caption_sources` table mapping `caption_source_id` → backend/model/created_at plus prompt hashes (not prompt text).
+
+Caption priority (waterfall) + planned usage:
+
+| # | variant | backend | model | planned_images |
+| --- | --- | --- | --- | --- |
+| 0 | caption_gemini |  |  | 34,898 |
+| 1 | caption_ministral_14b_2512 |  |  | 182,056 |
+
+Available caption variants (top 30):
+
+| selected | variant | images_with_ok_caption |
+| --- | --- | --- |
+| ✓ | caption_ministral_14b_2512 | 182,056 |
+| ✓ | caption_gemini | 34,898 |
+
+
+
+Missing caption policy: `drop`
+
+## Export summary
+
+- images_seen: 216,954
+- images_exported: 216,954
+- skipped_no_caption: 0
+- skipped_too_small: 0
+- decode_errors: 0
+- encode_errors: 0
+
+## Efficient loading
+
+### Recommended
+
+Treat this as a **webdataset-style** collection of tar shards:
+
+- Prefer **sequential reads** of tar files for throughput.
+- Shuffle at the **shard level** (and optionally within-shard) for good randomness without expensive random I/O.
+- Use `manifest.json` to list buckets and shards.
+
+#### Python (`webdataset`)
+
+```python
+import webdataset as wds
+
+urls = "buckets/*/shard-*.tar"  # glob; adjust if you want a single bucket only
+ds = (
+    wds.WebDataset(urls)
+    .decode("pil")            # decodes .jpg to PIL.Image
+    .to_tuple("jpg", "txt", "json")
+)
+for jpg, caption, meta in ds:
+    ...
+```
+
+#### Python (`tarfile`, no extra deps)
+
+```python
+import io, json, tarfile
+from pathlib import Path
+
+tar_path = next(Path("buckets").rglob("shard-*.tar"))
+with tarfile.open(tar_path, "r") as tf:
+    members = tf.getmembers()
+    for m in members:
+        if not m.name.endswith(".txt"):
+            continue
+        key = m.name[:-4]
+        caption = tf.extractfile(m).read().decode("utf-8").strip()
+        meta = json.loads(tf.extractfile(tf.getmember(key + ".json")).read().decode("utf-8"))
+        jpg_bytes = tf.extractfile(tf.getmember(key + ".jpg")).read()
+        ...
+```

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+{
+  "format": "bucketed_shards_v1",
+  "created_at": "2026-01-08T09:51:12.478529+00:00",
+  "export_id": "export-2026-01-08T09:51:12.478529+00:00",
+  "base_resolution": 512,
+  "divisible": 32,
+  "image_codec": {
+    "name": "jpeg",
+    "quality": 95,
+    "subsampling_policy": "adaptive_scale",
+    "adaptive_scale_threshold": 0.85
+  },
+  "crop": {
+    "strategy": "corner",
+    "allowed_corners": [
+      2,
+      3
+    ]
+  },
+  "caption_priority": [
+    {
+      "variant": "caption_gemini"
+    },
+    {
+      "variant": "caption_ministral_14b_2512"
+    }
+  ],
+  "missing_caption_policy": "drop",
+  "too_small_policy": "drop",
+  "export_settings": {
+    "shard_size": 1024,
+    "workers": 8
+  },
+  "proto_buckets_1024": [
+    {
+      "width": 512,
+      "height": 2048
+    },
+    {
+      "width": 640,
+      "height": 1536
+    },
+    {
+      "width": 640,
+      "height": 1600
+    },
+    {
+      "width": 704,
+      "height": 1408
+    },
+    {
+      "width": 704,
+      "height": 1472
+    },
+    {
+      "width": 768,
+      "height": 1280
+    },
+    {
+      "width": 768,
+      "height": 1344
+    },
+    {
+      "width": 832,
+      "height": 1152
+    },
+    {
+      "width": 832,
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