Initial commit

.gitattributes

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+*.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

Complementary/README.md

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+# 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.

Complementary/selection_manifest.csv

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+size 11475622

Complementary/summary.json

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+{
+  "script": "scripts/NTIRE/fill_hf_complementary_to_25k.py",
+  "script_version": "1.0",
+  "created_at_utc": "2026-08-27T13:22:53.907877+00:00",
+  "source_dataset": "NTIRE",
+  "dataset_path": "Complementary",
+  "label": 0,
+  "label_name": "real",
+  "build_mode": "validated_base_plus_staged_atomic_append",
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+  "rows_per_file": 2000,
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+  "selection": {
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+        "train-00003-of-00007.parquet",
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+        "train-append-shard4-00001-of-00007.parquet",
+        "train-append-shard4-00002-of-00007.parquet",
+        "train-append-shard4-00003-of-00007.parquet",
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+        "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
+  }
+}

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NTIRE/Fake/README.md

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+# 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.

NTIRE/Fake/selection_manifest.csv

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NTIRE/Fake/summary.json

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+{
+  "script": "scripts/NTIRE/build_hf_fake_dataset.py",
+  "script_version": "2.0",
+  "created_at_utc": "2026-08-27T01:28:34.943056+00:00",
+  "source_dataset": "NTIRE",
+  "label": 1,
+  "label_name": "fake",
+  "selection": {
+    "method": "dimension_filter_then_priority_then_labels_csv_order",
+    "random_sampling": false,
+    "priority": [
+      "shard_5",
+      "shard_1",
+      "shard_2"
+    ],
+    "target_rows": 50000,
+    "source_contributions": {
+      "shard_5": 13024,
+      "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"
+      }
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NTIRE/real/README.md

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+# 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.

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+{
+  "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"
+    ],
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+        "operator": ">",
+        "value": 512
+      },
+      "height": {
+        "operator": ">",
+        "value": 512
+      },
+      "duplicate_image_sha256": "excluded"
+    },
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+    "selection_sha256_method": "ordered_manifest_identity_records",
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+    "append_selection_sha256": "0318a03642c51df5d134a6f9501b4c3eb1bb45dd81e87c8f66ef896b75c6e7b5",
+    "duplicate_hashes_skipped_before_target": 0
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+  "rows_per_file": 2000,
+  "selected_source_bytes": 41241143060,
+  "source_inventories": {
+    "shard_5": {
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+      "labels_csv_sha256": "59684b97af007dbb6920930e297e3e8585355f4edb360983a218c08d87ff80c6",
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+      "labels_csv": "shard_2/labels.csv",
+      "labels_csv_sha256": "e67cf67eae7bc412597d06d0ba0484af6133216fc26f649753e2630be81297c8",
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+    }
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