Adopt PraNet 900/100 (Kvasir) and 550/62 (CVC) as canonical splits

README.md

@@ -97,12 +97,14 @@ MedSeg-7D/
 │   ├── TIF/                      original release format
 │   ├── metadata.csv              per-frame metadata
 │   ├── class_dict.csv
-│   └── video_split_seed42.json   CANONICAL video-level split (23 train / 6 test sequences)
+│   ├── pranet_split.json         PRIMARY: PraNet 550/62 image-level split (literature-standard)
+│   └── video_split_seed42.json   ALTERNATIVE: leakage-free 23/6 video-level split (more rigorous)
 │
 ├── Kvasir-SEG/                   (endoscopy polyp, 1000 images)
 │   ├── images/                   RGB frames
 │   ├── masks/                    binary masks
 │   ├── bbox/                     bounding boxes (auxiliary)
+│   ├── pranet_split.json         PRIMARY: PraNet 900/100 train/test split (literature-standard)
 │   └── kavsir_seg_README.md      original release notes
 │
 ├── REFUGE2/                      (fundus optic disc, 1200 images = 400 train + 400 val + 400 test)
@@ -175,10 +177,11 @@ Approximate total size: ~18 GB.
 | **Original task** | Polyp segmentation |
 | **Frames / video sequences** | 612 / 29 |
 | **Mask convention** | Binary polyp foreground |
-| **Split type (canonical)** | **Video-level**, 23 train / 6 test sequences, seed=42 (489 frames train, 123 frames test) |
-| **Split file** | `CVC-ClinicDB/video_split_seed42.json` |
-| **Image-level split** | Available *for backward compatibility with prior literature*, but **leaks same-video frames** across train/test — can inflate Dice ~20–24 points. Image-level is the convention in many older papers; if you must reproduce them, use their split, but understand it is leaky. |
-| **Recommendation** | New work should use the video-level split. |
+| **PRIMARY split (literature-standard)** | PraNet's **550/62** image-level train/test, used by PraNet, Polyp-PVT, SANet, ESFPNet and most polyp papers |
+| **Primary split file** | `CVC-ClinicDB/pranet_split.json` |
+| **ALTERNATIVE split (leakage-free)** | **Video-level**, 23 train / 6 test sequences, seed=42 (489 frames train, 123 frames test) |
+| **Alternative split file** | `CVC-ClinicDB/video_split_seed42.json` |
+| **Important note** | The PraNet split is image-level and **leaks same-video frames** across train/test (CVC has 29 underlying sequences). Use it for direct comparison to literature; use video-level for honest leakage-free generalization numbers. The two are not directly cross-comparable in absolute Dice. |
 | **Source** | [CVC-ClinicDB](https://polyp.grand-challenge.org/CVCClinicDB/) |
 | **Reference** | Bernal et al., *Computerized Medical Imaging and Graphics 2015* |
 | **License** | Released for academic use; cite the original paper. |
@@ -191,9 +194,10 @@ Approximate total size: ~18 GB.
 | **Original task** | Polyp segmentation |
 | **Images** | 1000 |
 | **Mask convention** | Binary polyp foreground |
-| **Split type (canonical)** | Image-level, 80/20, seed=42 |
-| **Leakage risk** | The release does not publish per-procedure metadata. Image-level is the community standard. |
-| **Note** | Auxiliary `bbox/` (bounding boxes) included from the original release. |
+| **PRIMARY split (literature-standard)** | PraNet's **900/100** train/test (specific file lists), used by PraNet, Polyp-PVT, SANet, ESFPNet and the entire polyp-segmentation literature |
+| **Primary split file** | `Kvasir-SEG/pranet_split.json` |
+| **Leakage risk** | The release does not publish per-procedure metadata. Image-level is the community standard; per-procedure leakage cannot be audited. |
+| **Note** | Filenames in our release use `.jpg` (the original Kvasir-SEG extension); PraNet ships them as `.png` after conversion — basenames match exactly. Auxiliary `bbox/` (bounding boxes) included from the original release. |
 | **Source** | [Kvasir-SEG](https://datasets.simula.no/kvasir-seg/) |
 | **Reference** | Jha et al., *MMM 2020* |
 | **License** | CC-BY-4.0 |
@@ -238,8 +242,8 @@ sensible. Summary:
 
 | Dataset | Mainstream literature default | HuggingFace community card | **Our default** | Verdict |
 |---|---|---|---|---|
-| CVC-ClinicDB | Image-level via PraNet's release files (550 train + 62 test pooled with Kvasir into 1450/100) | `Angelou0516/CVC-ClinicDB`: 80/10/10 image-level, ESFPNet split | Image-level 80/20 seed=42; **also a video-level 23/6-sequence split** is shipped | Matches PraNet practice; we additionally fix the same-video leakage that PraNet's image split exposes |
-| Kvasir-SEG | Image-level via PraNet's 900/100 release files | `kowndinya23/Kvasir-SEG`: 880/120 (no test) | Image-level 80/20 seed=42 | Close to mainstream; if you need PraNet-comparable numbers, use 900/100 instead |
+| CVC-ClinicDB | PraNet's **550/62** image-level files (de facto standard since 2020) | `Angelou0516/CVC-ClinicDB`: 80/10/10 image-level, ESFPNet split | **PraNet 550/62 (`pranet_split.json`) as primary; video-level 23/6 (`video_split_seed42.json`) as leakage-free alternative** | ✅ Matches PraNet exactly + adds a leakage-audit option that nobody else ships |
+| Kvasir-SEG | PraNet's **900/100** file list (de facto standard) | `kowndinya23/Kvasir-SEG`: 880/120 (no test) | **PraNet 900/100 (`pranet_split.json`)** | ✅ Matches PraNet exactly |
 | BUSI | Image-level random; growing minority does 5-fold + de-duplication (BUS-Set, Med Phys 2023, documents duplicate leakage) | n/a | Image-level 80/20 seed=42 | Matches majority; **flag**: BUSI release has documented duplicates, and patient IDs are not public, so true patient-level splits are not possible |
 | ISIC 2018 | Official 2594/100/1000 OR pooled 80/20 | varies | Official 2594/100/1000 preserved | Matches official challenge split |
 | REFUGE2 | Official 400/400/400 (train/val/test domain-shift design) | varies | Official train/val/test preserved | Matches official |
@@ -300,7 +304,17 @@ train_volumes = set(info["train_patients"])  # key name retained from original
 #       for img_path in glob.glob(f"{ROOT}/BraTS2020/images/{vol}/*.png"):
 #           ...
 
-# CVC (video-level — recommended) or image-level (legacy)
+# Kvasir-SEG (PraNet 900/100, literature standard)
+info = json.load(open(os.path.join(ROOT, "Kvasir-SEG", "pranet_split.json")))
+train_files = set(info["train_files"])  # 900 file basenames (.jpg)
+test_files  = set(info["test_files"])   # 100 file basenames (.jpg)
+
+# CVC-ClinicDB (PraNet 550/62, literature standard — has same-video leakage!)
+info = json.load(open(os.path.join(ROOT, "CVC-ClinicDB", "pranet_split.json")))
+train_files = set(info["train_files"])  # 550 frames as <n>.png
+test_files  = set(info["test_files"])   # 62 frames as <n>.png
+
+# CVC-ClinicDB (video-level 23/6, leakage-free alternative)
 info = json.load(open(os.path.join(ROOT, "CVC-ClinicDB", "video_split_seed42.json")))
 train_seqs = set(info["train_sequences"])
 ```
@@ -324,8 +338,8 @@ seg   = nib.load(os.path.join(pat, "BraTS2021_00000_seg.nii.gz")).get_fdata()
 # seg has 4 classes (0=BG, 1=necrotic, 2=edema, 4=enhancing); whole-tumor = (seg > 0)
 ```
 
-For datasets without a `split_info.json`, the canonical image-level split
-is reproducible from `seed=42`:
+For **BUSI**, the only dataset without a packaged split file, use a
+seed-fixed image-level 80/20 split:
 
 ```python
 import numpy as np
@@ -335,6 +349,9 @@ def get_image_level_split(n_images, seed=42, train_ratio=0.8):
     return perm[:n_train], perm[n_train:]
 ```
 
+(BUSI's release does not include patient IDs, so a true patient-level
+split is not possible. See per-dataset notes for caveats.)
+
 ---
 
 ## Known caveats and good practices