diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000000000000000000000000000000000000..89bac657b1aa1cdda28f6fecf7aaca217ac1180b --- /dev/null +++ b/.gitattributes @@ -0,0 +1,66 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.avro filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.lz4 filter=lfs diff=lfs merge=lfs -text +*.mds filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +# Audio files - uncompressed +*.pcm filter=lfs diff=lfs merge=lfs -text +*.sam filter=lfs diff=lfs merge=lfs -text +*.raw filter=lfs diff=lfs merge=lfs -text +# Audio files - compressed +*.aac filter=lfs diff=lfs merge=lfs -text +*.flac filter=lfs diff=lfs merge=lfs -text +*.mp3 filter=lfs diff=lfs merge=lfs -text +*.ogg filter=lfs diff=lfs merge=lfs -text +*.wav filter=lfs diff=lfs merge=lfs -text +# Image files - uncompressed +*.bmp filter=lfs diff=lfs merge=lfs -text +*.gif filter=lfs diff=lfs merge=lfs -text +*.png filter=lfs diff=lfs merge=lfs -text +*.tiff filter=lfs diff=lfs merge=lfs -text +# Image files - compressed +*.jpg filter=lfs diff=lfs merge=lfs -text +*.jpeg filter=lfs diff=lfs merge=lfs -text +*.webp filter=lfs diff=lfs merge=lfs -text +# Video files - compressed +*.mp4 filter=lfs diff=lfs merge=lfs -text +*.webm filter=lfs diff=lfs merge=lfs -text +NTIRE/Fake/selection_manifest.csv filter=lfs diff=lfs merge=lfs -text +NTIRE/real/selection_manifest.csv filter=lfs diff=lfs merge=lfs -text +Complementary/selection_manifest.csv filter=lfs diff=lfs merge=lfs -text +SID/real/selection_manifest.csv filter=lfs diff=lfs merge=lfs -text +SID/Fake/selection_manifest.csv filter=lfs diff=lfs merge=lfs -text +WildFake/Fake/selection_manifest.csv filter=lfs diff=lfs merge=lfs -text diff --git a/Complementary/README.md b/Complementary/README.md new file mode 100644 index 0000000000000000000000000000000000000000..e80c998e1fdeb4702610dfeda822e0ff06ebf9bc --- /dev/null +++ b/Complementary/README.md @@ -0,0 +1,25 @@ +# Complementary NTIRE Real images + +This prefix contains 25,000 additional NTIRE `label=0` Real +images. Every image has `width > 512` and +`height > 512`. The original 12,607 rows remain in +seven immutable `train-xxxxx-of-00007.parquet` files; the 12,393 +`shard_4` continuation is stored in seven +`train-append-shard4-xxxxx-of-00007.parquet` files. + +The append selection excludes every `sample_id` or image SHA-256 already in +the 50K `NTIRE/real` set or the original Complementary set. Original JPEG bytes +are embedded without re-encoding and every row matches profile +`d39db51fdcf2ed8c0f2148e77eb00b5f48d4993e8fa2d5e501a28188e1fd9f44`. + +```python +from datasets import load_dataset + +dataset = load_dataset( + "Edward0707/TechJam2026_Jamlai_Bench", + data_files={"train": "Complementary/train-*.parquet"}, +) +``` + +`selection_manifest.csv` contains row-level provenance and hashes; +`summary.json` records both immutable generations and their validation. diff --git a/Complementary/selection_manifest.csv b/Complementary/selection_manifest.csv new file mode 100644 index 0000000000000000000000000000000000000000..72443bae7d7552fa324e90ee94b23a67dba23b5e --- /dev/null +++ b/Complementary/selection_manifest.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:95dcdb26d7e952aebdaa5632a7e6805e94b04092da301aa25f64947bcf0e1c13 +size 11475622 diff --git a/Complementary/summary.json b/Complementary/summary.json new file mode 100644 index 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+ }, + "generations": { + "base_shard_0": { + "rows": 12607, + "parquet_files": 7, + "file_names": [ + "train-00000-of-00007.parquet", + "train-00001-of-00007.parquet", + "train-00002-of-00007.parquet", + "train-00003-of-00007.parquet", + "train-00004-of-00007.parquet", + "train-00005-of-00007.parquet", + "train-00006-of-00007.parquet" + ], + "manifest_sha256": "0a31e4873c56c07f5475142c9a916c2bc9535cd24e6b9699576bc8b2157ccdaa" + }, + "append_shard_4": { + "rows": 12393, + "parquet_files": 7, + "file_names": [ + "train-append-shard4-00000-of-00007.parquet", + "train-append-shard4-00001-of-00007.parquet", + "train-append-shard4-00002-of-00007.parquet", + "train-append-shard4-00003-of-00007.parquet", + "train-append-shard4-00004-of-00007.parquet", + "train-append-shard4-00005-of-00007.parquet", + "train-append-shard4-00006-of-00007.parquet" + ], + "source_inventory": { + "labels_csv": "shard_4/labels.csv", + "labels_csv_sha256": "8b3cd726d9b556ce40c0b854d867ef0b41eb5a8a139b20bf51ae5bf9f4e67341", + "total_rows": 50000, + "real_rows": 18070, + "fake_rows": 31930, + "eligible_real_rows": 17704, + "dimension_rejected_real_rows": 366, + "disk_image_files": 50000, + "dimension_filter": { + "width": "> 512", + "height": "> 512" + } + }, + "considered_rows_before_target": 12393, + "excluded_existing_ids_before_target": 0, + "excluded_existing_hashes_before_target": 0, + "excluded_existing_both_before_target": 0, + "duplicate_new_hashes_before_target": 0, + "selection_sha256": "522e7debd9a80f2364db8e3f7568ba4dc0c7c38411e04f69346e8ff200d421ff" + } + }, + "exclusion_manifests": { + "ntire_real_50k": { + "path": "data/hf/transactions/.ntire_real_fill50k_upload.work/selection_manifest.csv", + "rows": 50000, + "sha256": "3ceb73d6ea5e64f913492c45fbdade8f8ebfdd73146ee145b7859e1796ff2336" + }, + "complementary_base": { + "path": "data/hf/transactions/.ntire_complementary_upload.work/selection_manifest.csv", + "rows": 12607, + "sha256": "0a31e4873c56c07f5475142c9a916c2bc9535cd24e6b9699576bc8b2157ccdaa" + } + }, + "jpeg_profile_matching": { + "distribution_path": "data/manifests/selected/ntire_fake50k_jpeg_profiles_all.distribution.json", + "distribution_sha256": "1519ada14275f0c5e3020242cc7f8e7b4f14e92ce718d05321f4ad9137990e71", + "schema_version": 1, + "profile_count": 1, + "target_profile_id": "d39db51fdcf2ed8c0f2148e77eb00b5f48d4993e8fa2d5e501a28188e1fd9f44", + "target_profile_source_count": 50000, + "checked_rows": 25000, + "all_rows_match": true + }, + "verification": { + "status": "passed", + "verified_rows": 25000, + "unique_sample_ids": 25000, + "unique_image_sha256": 25000, + "all_labels_equal_zero": true, + "all_images_jpeg": true, + "all_source_bytes_preserved": true, + "all_dimensions_passed": true, + "all_jpeg_profiles_match": true + }, + "upload": { + "strategy": "bounded_parallel_staging_then_atomic_copy_and_metadata", + "base_parquet_hashes_verified": 7, + "append_parquet_hashes_verified": 7, + "temporary_parquet_retention": "removed_only_after_remote_hash_match", + "staging_objects_cleaned_after_publish": true, + "root_readme_modified": false, + "ntire_prefix_modified": false + } +} diff --git a/Complementary/train-00000-of-00007.parquet b/Complementary/train-00000-of-00007.parquet new file mode 100644 index 0000000000000000000000000000000000000000..21eaf9b733667a5429d3416dd110a3381459e6e3 --- /dev/null +++ b/Complementary/train-00000-of-00007.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0d3d43a925854ac65a6bced7b3393c16dcb1c00c59979c2794cb81c8a2799f2e +size 1580404411 diff --git a/Complementary/train-00001-of-00007.parquet b/Complementary/train-00001-of-00007.parquet new file mode 100644 index 0000000000000000000000000000000000000000..2d0c905dbdef98a83688ca9972e8336fc74622bb --- /dev/null +++ b/Complementary/train-00001-of-00007.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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+1,36 @@ +# NTIRE / Fake + +This folder contains 50,000 NTIRE images with `label=1` (fake), +`width > 512`, and +`height > 512`. Original JPEG bytes are embedded +directly in the Parquet `image` column; the builder did not decode and re-encode +them. + +## Deterministic selection + +After applying the strict dimension filter, rows were taken without random +sampling, preserving each `labels.csv` order: + +- `shard_5`: 13,024 +- `shard_1`: 23,732 +- `shard_2`: 13,244 + +Total: 50,000 images. + +## Load with Datasets + +```python +from datasets import load_dataset + +dataset = load_dataset( + "Edward0707/TechJam2026_Jamlai_Bench", + data_files={"train": "NTIRE/Fake/train-*.parquet"}, +) +``` + +`selection_manifest.csv` records every source row, output Parquet row, image +dimensions, and SHA-256 digest. `summary.json` records source inventories, +selection counts, Parquet file checksums, and verification results. + +Before making a public redistribution, verify that the source dataset license +and attribution terms permit it. diff --git a/NTIRE/Fake/selection_manifest.csv b/NTIRE/Fake/selection_manifest.csv new 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"shard_1": 23732, + "shard_2": 13244 + }, + "filters": { + "label": { + "operator": "=", + "value": 1 + }, + "width": { + "operator": ">", + "value": 512 + }, + "height": { + "operator": ">", + "value": 512 + } + } + }, + "total_rows": 50000, + "parquet_files": 25, + "rows_per_file": 2000, + "selected_source_bytes": 12988282319, + "source_inventories": { + "shard_5": { + "labels_csv": "shard_5/labels.csv", + "labels_csv_sha256": "59684b97af007dbb6920930e297e3e8585355f4edb360983a218c08d87ff80c6", + "total_rows": 27643, + "real_rows": 9947, + "fake_rows": 17696, + "eligible_fake_rows": 13024, + "dimension_rejected_fake_rows": 4672, + "disk_image_files": 27643, + "dimension_filter": { + "width": "> 512", + "height": "> 512" + } + }, + "shard_1": { + "labels_csv": "shard_1/labels.csv", + "labels_csv_sha256": "0ff11a17baa5abdaa7be0d0267aff0d9714abc98b0af27bc3b633d68ff20a6d4", + "total_rows": 50000, + "real_rows": 18087, + "fake_rows": 31913, + "eligible_fake_rows": 23732, + 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b/NTIRE/Fake/train-00024-of-00025.parquet new file mode 100644 index 0000000000000000000000000000000000000000..25acd4e9a4f2e2f3488fecfa19cfdea3c1933e14 --- /dev/null +++ b/NTIRE/Fake/train-00024-of-00025.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:865b383624842cac454d29c51021cc464808f3ad41a4ac240085f345262d562e +size 497965267 diff --git a/NTIRE/real/README.md b/NTIRE/real/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c82303fe991915c3d5971e64c94fe5534fbc7718 --- /dev/null +++ b/NTIRE/real/README.md @@ -0,0 +1,31 @@ +# NTIRE / real + +This prefix contains 50,000 NTIRE images with `label=0` +(`real`), `width > 512`, and +`height > 512`. Original JPEG bytes are embedded in the +Parquet `image` column without JPEG-to-JPEG re-encoding. + +All rows match the single JPEG profile declared by +`data/manifests/selected/ntire_fake50k_jpeg_profiles_all.distribution.json`. The matching profile ID is +`d39db51fdcf2ed8c0f2148e77eb00b5f48d4993e8fa2d5e501a28188e1fd9f44`. + +The original 44,993-row generation remains in its 23 immutable Parquet files. +The 5,007-row `shard_0` continuation is stored in three +`train-append-shard0-*.parquet` files. The glob below loads both generations. + +```python +from datasets import load_dataset + +dataset = load_dataset( + "Edward0707/TechJam2026_Jamlai_Bench", + data_files={"train": "NTIRE/real/train-*.parquet"}, +) +``` + +`selection_manifest.csv` records source/output provenance, dimensions, image +SHA-256, source JPEG profile, and profile-match status for every row. +`summary.json` records both immutable generations and their complete validation +declarations. + +Before public redistribution, verify that the source dataset license and +attribution terms permit it. diff --git a/NTIRE/real/selection_manifest.csv b/NTIRE/real/selection_manifest.csv new file mode 100644 index 0000000000000000000000000000000000000000..a255383db816e7364af93fb7e3b989aba3055192 --- /dev/null +++ b/NTIRE/real/selection_manifest.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3ceb73d6ea5e64f913492c45fbdade8f8ebfdd73146ee145b7859e1796ff2336 +size 19681782 diff --git a/NTIRE/real/summary.json b/NTIRE/real/summary.json new file mode 100644 index 0000000000000000000000000000000000000000..928cb8c487a2798bbb3c92993759b6d5e03c4454 --- /dev/null +++ b/NTIRE/real/summary.json @@ -0,0 +1,354 @@ +{ + "script": "scripts/NTIRE/fill_hf_real_to_50k.py", + "script_version": "1.0", + "created_at_utc": "2026-08-27T08:22:01.497860+00:00", + "source_dataset": "NTIRE", + "dataset_path": "NTIRE/real", + "label": 0, + "label_name": "real", + "build_mode": "streamed_base_plus_atomic_append", + "selection": { + "method": "preserve_validated_base_then_dimension_filter_then_labels_csv_order_excluding_duplicate_image_sha256", + "random_sampling": false, + "priority": [ + "shard_5", + "shard_1", + "shard_2", + "shard_0" + ], + "target_count_argument": 50000, + "eligible_rows_across_sources": 62607, + "selected_rows": 50000, + "source_contributions": { + "shard_5": 9764, + "shard_1": 17701, + "shard_2": 17528, + "shard_0": 5007 + }, + "filters": { + "label": { + "operator": 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+version https://git-lfs.github.com/spec/v1 +oid sha256:ecf8c7a9cfc188def6a133ee39586a25d7c842edc1b343027d06ef143c6b1c70 +size 843173358 diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ff7c3377cfbeb951cb796c0f634e7f362e3ea709 --- /dev/null +++ b/README.md @@ -0,0 +1,42 @@ +--- +configs: + - config_name: ntire_fake + data_files: + - split: train + path: "NTIRE/Fake/train-*.parquet" +--- + +# TechJam2026 Jamlai Bench + +This repository collects image data used to build the TechJam2026 Jamlai +benchmark. + +## NTIRE / Fake + +The `ntire_fake` configuration contains 50,000 NTIRE images labeled as fake. +They are stored under `NTIRE/Fake/` as self-contained Parquet shards with the +original JPEG bytes embedded in the `image` column. Every selected image +satisfies both `width > 512` and `height > 512`. + +After applying the strict dimension filter, the deterministic selection +preserves each source `labels.csv` order: + +- `shard_5`: 13,024 images +- `shard_1`: 23,732 images +- `shard_2`: 13,244 images + +```python +from datasets import load_dataset + +dataset = load_dataset( + "Edward0707/TechJam2026_Jamlai_Bench", + "ntire_fake", +) +``` + +The per-sample provenance and SHA-256 values are recorded in +`NTIRE/Fake/selection_manifest.csv`. Build and verification details are in +`NTIRE/Fake/summary.json`. + +Before redistributing these images, verify the source dataset's license and +attribution requirements. diff --git a/SID/Fake/README.md b/SID/Fake/README.md new file mode 100644 index 0000000000000000000000000000000000000000..8f7eef57c44f2cb311e2f69ce0892b6c77c95ec1 --- /dev/null +++ b/SID/Fake/README.md @@ -0,0 +1,51 @@ +# SID/Fake + +This prefix contains 27,380 images from SID_Set with +`label=1` (`fake`). + +**These JPEG bytes are not the source bytes.** The source images are lossless +PNG, and shipping them as PNG next to JPEG real images would hand any classifier +the file format as a perfect shortcut. Each image was therefore encoded exactly +once from its PNG master, with the encoder settings drawn from the measured +distribution of `SID/real`: 2,431 distinct profiles over 26,131 real images, +allocated by exact largest-remainder proportion rather than by i.i.d. draws. +The resulting profile distribution sits at total variation 0.0061 from the real +side. Matching only the format would have moved the shortcut from "which +format" to "which quantization table", and that one is baked into the pixels. + +## Selection + +label=1; every SID_Set FLUX row; PNG master re-encoded to a profile drawn from the real side + +- `flux`: 27,380 + +Total: 27,380 images. + +## Dimensions + +Every image is exactly 1024x1024, so the `width > 512 AND height > 512` filter +the `NTIRE/*` and `Complementary` prefixes apply would have kept all of them +unchanged. Train with native-scale random cropping rather than resizing -- +resampling is itself a signal, and one this set would carry and the real side +would not. + +## Load with Datasets + +```python +from datasets import load_dataset + +dataset = load_dataset( + "TechJam2026-Jamlai-Bench/TechJam2026_Jamlai_Bench", + data_files={"train": "SID/Fake/train-*.parquet"}, +) +``` + +The Parquet schema is identical to the `NTIRE/*` prefixes: the same sixteen columns in +the same order, so the prefixes concatenate. Everything specific to this set -- +generator, source archive, the JPEG profile actually applied -- lives in +`selection_manifest.csv` instead, which also records every source row, output Parquet +row, image dimensions, and SHA-256 digest. `summary.json` records the selection rule, +per-file checksums, and verification results. + +Before making a public redistribution, verify that the source dataset license and +attribution terms permit it. diff --git a/SID/Fake/selection_manifest.csv b/SID/Fake/selection_manifest.csv new file mode 100644 index 0000000000000000000000000000000000000000..5a5929be5722b94666157d87bbf836c0a9b1dbd0 --- /dev/null +++ b/SID/Fake/selection_manifest.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2b574af2f81454ea9956a81f5442ae601cf125f0ff170eb1d16af7234207948a +size 12997668 diff --git a/SID/Fake/summary.json b/SID/Fake/summary.json new file mode 100644 index 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Dimensions + +The `NTIRE/*` and `Complementary` prefixes filter on `width > 512 AND height > 512`. +This prefix uses a short-edge bound of `>= 512` instead, so images that are exactly +512 on one side are kept: short edge min 512, median 687, max 4000, +with 20 images (0.1%) at exactly 512. Train with native-scale random +cropping rather than resizing -- resampling is itself a signal. + +## Load with Datasets + +```python +from datasets import load_dataset + +dataset = load_dataset( + "TechJam2026-Jamlai-Bench/TechJam2026_Jamlai_Bench", + data_files={"train": "SID/real/train-*.parquet"}, +) +``` + +The Parquet schema is identical to the `NTIRE/*` prefixes: the same sixteen columns in +the same order, so the prefixes concatenate. Everything specific to this set -- +generator, source archive, the JPEG profile actually applied -- lives in +`selection_manifest.csv` instead, which also records every source row, output Parquet +row, image dimensions, and SHA-256 digest. `summary.json` records the selection rule, +per-file checksums, and verification results. + +Before making a public redistribution, verify that the source dataset license and +attribution terms permit it. diff --git a/SID/real/selection_manifest.csv b/SID/real/selection_manifest.csv new file mode 100644 index 0000000000000000000000000000000000000000..327797bb5b0f36d54b6066cbe36081ea2501a791 --- /dev/null +++ b/SID/real/selection_manifest.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e484c21e32fa88680b2cf819a5ecf11db461115cadfbbce99d6016fa8c5c39c0 +size 11556160 diff --git a/SID/real/summary.json b/SID/real/summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c747ce634108fbf3e3d10a698f3d494091ae0f1a --- /dev/null +++ b/SID/real/summary.json @@ -0,0 +1,144 @@ +{ + "script": "hf_publish.py", + "script_version": "1.0", + "created_at_utc": "2026-08-28T03:43:39.469733+00:00", + "source_dataset": "SID_Set", + "dataset_path": "SID/real", + "label": 0, + "label_name": "real", + "selection": { + "method": "all_retained_rows_in_shard_then_manifest_order", + "random_sampling": false, + "target_rows": 27076, + "source_contributions": { + "openimages_v7": 27076 + }, + "filters": { + "label": { + "operator": "=", + "value": 0 + }, + "short_edge": { + "operator": ">=", + "value": 512 + } + }, + "short_edge_stats": { + "min": 512, + "median": 687, + "max": 4000, + "exactly_512": 20 + } + }, + "total_rows": 27076, + "parquet_files": 14, + "rows_per_file": 2000, + "selected_source_bytes": 8445272288, + "image_bytes_origin": "original source bytes, not decoded or re-encoded", + "files": [ + { + "path": "train-00000-of-00014.parquet", + "rows": 2000, + "size_bytes": 627044943, + "sha256": "80d221726f8b768d2c1f960303e9dec9e254ad0a557e33aaa7c38ac97e5b3eeb" + }, + { + "path": "train-00001-of-00014.parquet", + "rows": 2000, + "size_bytes": 625055724, + "sha256": "d561b7cf40038be536dc1b2a40bad2c2b0eb1bb063f5e712665b73c5592629c1" + }, + { + "path": "train-00002-of-00014.parquet", + "rows": 2000, + "size_bytes": 614162557, + "sha256": "cd6d09beabe07937a0bc942c95fbb2f972d3a03c94aafc3f8d67484c63066ce4" + }, + { + "path": "train-00003-of-00014.parquet", + "rows": 2000, + "size_bytes": 625947596, + "sha256": "b81b7f0bf77f0371799b8241c5e1065136b9089d7a3c11923ff67f8967d19e07" + }, + { + "path": "train-00004-of-00014.parquet", + "rows": 2000, + "size_bytes": 609956186, + "sha256": "3490667c3627ab615f19a03f0a3ad9c6bcb7f66dff3a5a3475bf30a355d72611" + }, + { + "path": "train-00005-of-00014.parquet", + "rows": 2000, + "size_bytes": 615291055, + "sha256": "6afe055fe54198aebac52aacba6d7aab5ba478718c511b72329461261121d5cf" + }, + { + "path": "train-00006-of-00014.parquet", + "rows": 2000, + "size_bytes": 626110392, + "sha256": "80fcb203b2a1f5c89125d735c41ea97fc9b42617922d196904f436647d9788c2" + }, + { + "path": "train-00007-of-00014.parquet", + "rows": 2000, + "size_bytes": 630380662, + "sha256": "58b112df1fc5e4d817f4b93ecabefd2aec647abb9e0c7d5d9b409af0faed1157" + }, + { + "path": "train-00008-of-00014.parquet", + "rows": 2000, + "size_bytes": 633372805, + "sha256": "ed4725c1a86b3b3f0e136224a9e4a199e27d56031ca0519030d6ec47d4f9d2dc" + }, + { + "path": "train-00009-of-00014.parquet", + "rows": 2000, + "size_bytes": 604922654, + "sha256": "19846e7ca39408155874e164536e5a720b52a9d22cdc349d459cd7777aff3d31" + }, + { + "path": "train-00010-of-00014.parquet", + "rows": 2000, + "size_bytes": 633106598, + "sha256": "d56996d8258e95bb9a54c78b3733df51a1b8f621401b3a47f6357e4809b36340" + }, + { + "path": "train-00011-of-00014.parquet", + "rows": 2000, + "size_bytes": 624685757, + "sha256": "d1b379d3b3b2ce7983ed8ca4f347f88a6649693cf4eaaa13f25c18a4e145f569" + }, + { + "path": "train-00012-of-00014.parquet", + "rows": 2000, + "size_bytes": 640826435, + "sha256": "cc99b9435f852da9cf3a3729252bec18d873ac030afd0baf7e31263ea6022c48" + }, + { + "path": "train-00013-of-00014.parquet", + "rows": 1076, + "size_bytes": 335193477, + "sha256": "cc6d2c57e439ddcd36c695e4df6850b46ef1bf00dd7efa13a88cc00e372e2c22" + } + ], + "manifest": { + "path": "selection_manifest.csv", + "rows": 27076, + "size_bytes": 11556160 + }, + "verification": { + "status": "passed", + "verified_rows": 27076, + "parquet_files_checked": 14, + "schema_matches_ntire_layout": true, + "huggingface_metadata_matches": true, + "image_path_null_on_every_row": true, + "embedded_image_sha256_checked": 27076, + "unique_image_sha256": 27076, + "all_labels_equal_0": true, + "manifest_rows_checked": 27076, + "source_bytes_identity_sampled": 300, + "all_source_bytes_preserved": true, + 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b/WildFake/Fake/README.md new file mode 100644 index 0000000000000000000000000000000000000000..fca8527834d33948bd80938bb7e6d2fff1f55018 --- /dev/null +++ b/WildFake/Fake/README.md @@ -0,0 +1,65 @@ +# WildFake/Fake + +This prefix contains 24,982 images from WildFake with +`label=1` (`fake`). + +**These JPEG bytes are not the source bytes.** The source images are lossless +PNG, and shipping them as PNG next to JPEG real images would hand any classifier +the file format as a perfect shortcut. Each image was therefore encoded exactly +once from its PNG master, using the single JPEG profile carried by the +real images these fakes train against -- `Complementary` and `NTIRE/real`, both +of which declare profile `d39db51fdcf2ed8c0f2148e77eb00b5f48d4993e8fa2d5e501a28188e1fd9f44` +with `all_rows_match: true`. That profile was originally measured on +`NTIRE/Fake`, which is why the source file is named for it; the target here is +the real side. Encoding replays the qtable set value for value (reverse-lookup: +IJG quality 95) at 4:2:0 chroma, baseline. The lossless masters were never +JPEG-compressed, so every row carries exactly one JPEG generation. + +The source file is a marginal and says so -- it omits component selectors, +subsampling, and progressive mode. Subsampling was confirmed separately with the +NTIRE side; progressive, Huffman optimisation, JFIF density and ICC were left at +the encoder's defaults and are **not** verified against the target. Only qtables +and subsampling change decoded pixels, so the pixel-level alignment is exact and +the unverified fields affect file bytes only. `summary.json` records the split. + +## Selection + +label=1; per-generator quota; PNG master re-encoded to the single NTIRE fake profile + +- `SD-original`: 6,000 +- `Midjourney`: 5,988 +- `SD-personalized`: 4,000 +- `SD-adaptor`: 4,000 +- `Imagen`: 3,000 +- `GigaGAN`: 1,994 + +Total: 24,982 images. + +## Dimensions + +The `NTIRE/*` and `Complementary` prefixes filter on `width > 512 AND height > 512`. +This prefix uses a short-edge bound of `>= 512` instead, so images that are exactly +512 on one side are kept: short edge min 512, median 512, max 2048, +with 17,603 images (70.5%) at exactly 512. Train with native-scale random +cropping rather than resizing -- resampling is itself a signal. + +## Load with Datasets + +```python +from datasets import load_dataset + +dataset = load_dataset( + "TechJam2026-Jamlai-Bench/TechJam2026_Jamlai_Bench", + data_files={"train": "WildFake/Fake/train-*.parquet"}, +) +``` + +The Parquet schema is identical to the `NTIRE/*` prefixes: the same sixteen columns in +the same order, so the prefixes concatenate. Everything specific to this set -- +generator, source archive, the JPEG profile actually applied -- lives in +`selection_manifest.csv` instead, which also records every source row, output Parquet +row, image dimensions, and SHA-256 digest. `summary.json` records the selection rule, +per-file checksums, and verification results. + +Before making a public redistribution, verify that the source dataset license and +attribution terms permit it. diff --git a/WildFake/Fake/selection_manifest.csv b/WildFake/Fake/selection_manifest.csv new file mode 100644 index 0000000000000000000000000000000000000000..e366b3f51b9f8b191f9024f015bd2c02b1c8d40f --- /dev/null +++ b/WildFake/Fake/selection_manifest.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c4b6879810424fbaf4bdd66964620e56ffb083de135538ea245ce54bdd7b5627 +size 13525400 diff --git a/WildFake/Fake/summary.json b/WildFake/Fake/summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f38b9c042894ded442c4f2307f59a1f111ae4dcb --- /dev/null +++ b/WildFake/Fake/summary.json @@ -0,0 +1,185 @@ +{ + "script": "hf_publish.py", + "script_version": "1.0", + "created_at_utc": "2026-08-28T03:44:25.307457+00:00", + "source_dataset": "WildFake", + "dataset_path": "WildFake/Fake", + "label": 1, + "label_name": "fake", + "selection": { + "method": "per_generator_quota_then_manifest_order", + "random_sampling": false, + "target_rows": 24982, + "source_contributions": { + "GigaGAN": 1994, + "Imagen": 3000, + "Midjourney": 5988, + "SD-original": 6000, + "SD-personalized": 4000, + "SD-adaptor": 4000 + }, + "filters": { + "label": { + "operator": "=", + "value": 1 + }, + "short_edge": { + "operator": ">=", + "value": 512 + } + }, + "short_edge_stats": { + "min": 512, + "median": 512, + "max": 2048, + "exactly_512": 17603 + } + }, + "total_rows": 24982, + "parquet_files": 13, + "rows_per_file": 2000, + "selected_source_bytes": 4480628105, + "image_bytes_origin": "re-encoded from the lossless PNG master, exactly one JPEG generation", + "files": [ + { + "path": "train-00000-of-00013.parquet", + "rows": 2000, + "size_bytes": 189578530, + "sha256": "f1a48d243cb20cd219ccb076ff9b87a7027f371a2188140e5a38f031db032a3a" + }, + { + "path": "train-00001-of-00013.parquet", + "rows": 2000, + "size_bytes": 168365364, + "sha256": "aae061f54efebdfe40ee14922bb71cf9fc8c33393f5e8540856deedb61f616ee" + }, + { + "path": "train-00002-of-00013.parquet", + "rows": 2000, + "size_bytes": 429062715, + "sha256": "5d93134c05468bd6b86443e92a39fb1a76948e55f84a7200064397fe73f72f88" + }, + { + "path": "train-00003-of-00013.parquet", + "rows": 2000, + "size_bytes": 703771109, + "sha256": "f63c5274eebef4c0d6789d79f8d7450e0ec6ccf5a4222e46a5cc2b2789e985d2" + }, + { + "path": "train-00004-of-00013.parquet", + "rows": 2000, + "size_bytes": 562097882, + "sha256": "ca94875104462475c2410f1fa39af908da56d236fd28dbbad2cc77aba5d56673" + }, + { + "path": "train-00005-of-00013.parquet", + "rows": 2000, + "size_bytes": 649486842, + "sha256": "bee053b24472129383361a0e05857671562926008be59974449a733e1bedb367" + }, + { + "path": "train-00006-of-00013.parquet", + "rows": 2000, + "size_bytes": 704543739, + "sha256": "94dc035916fa490831ace9a73a9fed628146f650fffc8feb7a89813058fb6fdd" + }, + { + "path": "train-00007-of-00013.parquet", + "rows": 2000, + "size_bytes": 221880047, + "sha256": "acc1fa58605da416dbd24721b9783cf695fba6301152990776286239aab8b125" + }, + { + "path": "train-00008-of-00013.parquet", + "rows": 2000, + "size_bytes": 209929361, + "sha256": "9c3e968b117f05c394d21ff13fce2563e05adcb27cadff617cfd355ad4954245" + }, + { + "path": "train-00009-of-00013.parquet", + "rows": 2000, + "size_bytes": 196695851, + "sha256": "290442433fce291642526e9c08a2516e63ee7fe7d986ddeb8d9f6cfc88385ae7" + }, + { + "path": "train-00010-of-00013.parquet", + "rows": 2000, + "size_bytes": 186640286, + "sha256": "4b79eff747616c68218e843e53960c101e194012f96ac6283639aa55dfb26bca" + }, + { + "path": "train-00011-of-00013.parquet", + "rows": 2000, + "size_bytes": 175209946, + "sha256": "6384795e501a9fc3d7227dd330ee85dd620bd661225d3bf1dc178dd225511932" + }, + { + "path": "train-00012-of-00013.parquet", + "rows": 982, + "size_bytes": 86628816, + "sha256": "68b762ee9ca9cb7e741fc52a52d651101d61f3f5b5de7740d8327378e0b4cd34" + } + ], + "manifest": { + "path": "selection_manifest.csv", + "rows": 24982, + "size_bytes": 13525400 + }, + "jpeg_profile_alignment": { + "target": "Complementary / NTIRE/real", + "target_profile_id": "d39db51fdcf2ed8c0f2148e77eb00b5f48d4993e8fa2d5e501a28188e1fd9f44", + "target_provenance": "profile measured on NTIRE/Fake 50k; NTIRE/real (50,000) and Complementary (25,000) were both selected to match it, each declaring all_rows_match: true", + "profile_source": "ntire_fake50k_jpeg_profiles_all.qtables.json", + "profile_count": 1, + "jpeg_generations": 1, + "declared_by_source": { + "qtable_set_id": "d9093688c012bfa984fb8904a6b6eaa9ee9c18991f78cd2674a728f9aa89ec32", + "qtables": "replayed value for value; reverse-lookup identifies IJG quality 95" + }, + "supplied_by_builder": { + "subsampling": { + "value": 2, + "chroma": "4:2:0", + "basis": "confirmed by the NTIRE side" + }, + "progressive": { + "value": false, + "basis": "Pillow default, not verified against the target" + }, + "huffman": { + "value": "standard", + "basis": "Pillow default, not verified against the target" + }, + "jfif": { + "value": { + "unit": 0, + "density": [ + 1, + 1 + ] + }, + "basis": "Pillow default, not verified" + }, + "icc": { + "value": null, + "basis": "not considered" + } + }, + "alignment_scope": "pixel-level: exact. Only qtables and subsampling change decoded pixels and both match. 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