path stringlengths 21 59 | bytes unknown | mime_type stringclasses 3
values | width int32 49 8.26k | height int32 33 7.36k | size_bytes int64 6.26k 13.6M | sha256 stringlengths 64 64 |
|---|---|---|---|---|---|---|
images/crops/p2r_03001_crop_zoom.jpg | [
255,
216,
255,
224,
0,
16,
74,
70,
73,
70,
0,
1,
1,
0,
0,
1,
0,
1,
0,
0,
255,
219,
0,
67,
0,
2,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
2,
2,
2,
2,
4,
3,
2,
2,
2,
2,
5,
4,
4,
3,
4,
6,
5,
6,
6,
6,
5,
6,
6,
6,
... | image/jpeg | 336 | 157 | 18,172 | f32a1e3bf46c07d5bbd079ec012f5efca3fec574d0e456750cc3a17f96ac1196 |
images/crops/p2r_03005_crop_zoom.jpg | [
255,
216,
255,
224,
0,
16,
74,
70,
73,
70,
0,
1,
1,
0,
0,
1,
0,
1,
0,
0,
255,
219,
0,
67,
0,
2,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
2,
2,
2,
2,
4,
3,
2,
2,
2,
2,
5,
4,
4,
3,
4,
6,
5,
6,
6,
6,
5,
6,
6,
6,
... | image/jpeg | 572 | 354 | 71,516 | 41c2d888c35f56517df4d1a20e4201cea955b660fabe06cb5a5f910049a215f3 |
images/crops/p2r_03006_crop_zoom.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | image/jpeg | 768 | 265 | 111,869 | 10fa359adf660496ac6cbad1333dd576395ae65520ed765a78250579d7f04cab |
images/crops/p2r_03010_crop_zoom.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | image/jpeg | 284 | 336 | 25,059 | aa292fa3b5772fdc87d2c35eab5591e4efa22d609caa288b1996fac600fb4d0c |
images/crops/p2r_03012_crop_zoom.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | image/jpeg | 288 | 768 | 90,044 | 781fb3be56ff100761ae34fa5b43653d4abecc66738ace87131cfcc8c5618849 |
images/crops/p2r_03016_crop_zoom.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | image/jpeg | 312 | 456 | 40,100 | 184448fad796bf91a9c6e27d323fca90c72100b242906c48d26e5a64af43e1b4 |
images/crops/p2r_03021_crop_zoom.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | image/jpeg | 150 | 340 | 23,630 | 3817eb736e9580beef85d9f0bee1840f70eb59a63330f3ffa2380443b4bf52e1 |
images/crops/p2r_03029_crop_zoom.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | image/jpeg | 384 | 168 | 23,716 | d2fb55b99c47bf8b35680ccd841811d3193738dd06ce8c61e69846f293622ca3 |
images/crops/p2r_03040_crop_zoom.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | image/jpeg | 336 | 159 | 12,492 | e972142ef8cf5f8ebef5d0b292cfab0d11de786be05725e3185d965488a2cd19 |
images/crops/p2r_03045_crop_zoom.jpg | "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQo(...TRUNCATED) | image/jpeg | 391 | 768 | 139,675 | 02f31e1f6178b15257024b8b40b902d10b74850c6657159cc983c1346730cf4d |
End of preview. Expand in Data Studio
Visual_Agent Parquet
Parquet distribution of albert13200/Visual_Agent with 3679 tool-use
trajectories and 4816 deduplicated images.
Tables
samples: one row per trajectory.record_jsonpreserves the complete original row.images: one row per unique relative image path, with binary bytes, MIME type, dimensions, file size, and SHA-256.synthetic_attribute_samples: 5,000 synthetic SAM3 crop-replay attribute trajectories, kept separate asfirst_1000andremaining_4000splits.synthetic_attribute_images: the 10,000 referenced synthetic input/crop images, partitioned to match the two synthetic sample splits.
Separating the tables prevents the same image bytes from being embedded repeatedly when multiple trajectories reference one image.
Use directly
from datasets import load_dataset
samples = load_dataset("albert13200/Visual_Agent_Parquet", "samples", split="train")
images = load_dataset("albert13200/Visual_Agent_Parquet", "images", split="train")
synthetic_first = load_dataset(
"albert13200/Visual_Agent_Parquet",
"synthetic_attribute_samples",
split="first_1000",
)
synthetic_remaining = load_dataset(
"albert13200/Visual_Agent_Parquet",
"synthetic_attribute_samples",
split="remaining_4000",
)
Restore the path-based training layout
uvx --from huggingface-hub hf download \
albert13200/Visual_Agent_Parquet \
--repo-type dataset \
--local-dir Visual_Agent_Parquet
uv run --with pyarrow \
Visual_Agent_Parquet/materialize_visual_agent_parquet.py \
--input-root Visual_Agent_Parquet \
--output-root Visual_Agent
This writes Visual_Agent/training_trajectories_natural/ with the combined JSONL and
all relative image files expected by the existing training pipeline. Image bytes are
validated against their stored SHA-256 before use.
Restore the synthetic attribute set
uv run --with pyarrow \
Visual_Agent_Parquet/synthetic_attribute/materialize_synthetic_attribute_parquet.py \
--input-root Visual_Agent_Parquet/synthetic_attribute \
--output-root Synthetic_Attribute
Use --partition first_1000 or --partition remaining_4000 to restore only one
synthetic partition. Without --partition, the script restores all 5,000 rows and
verifies that the combined JSONL exactly matches the source SHA-256.
- Downloads last month
- 134