Add academic polish: inference example, hparams, CITATION.cff, dataset figures, per-class CSVs

.gitattributes

@@ -59,3 +59,5 @@ gradcam/gradcam_inception_v3.png filter=lfs diff=lfs merge=lfs -text
 gradcam/gradcam_resnet101.png filter=lfs diff=lfs merge=lfs -text
 gradcam/gradcam_resnet50.png filter=lfs diff=lfs merge=lfs -text
 gradcam/gradcam_vgg19.png filter=lfs diff=lfs merge=lfs -text
+dataset/class_distribution.png filter=lfs diff=lfs merge=lfs -text
+dataset/sample_grid.png filter=lfs diff=lfs merge=lfs -text

CITATION.cff

@@ -0,0 +1,35 @@
+cff-version: 1.2.0
+message: "If you use this benchmark or any of the trained models, please cite it as below."
+title: "Fundus 9-Model Benchmark: VGG19, ResNet50/101, DenseNet121, InceptionV3, Swin-B, CLIP, DINOv2-L, RETFound"
+authors:
+  - family-names: Katiyo
+    given-names: Daryl Panashe
+    affiliation: Xidian University
+version: "1.0.0"
+date-released: 2026-05-26
+license: Apache-2.0
+type: software
+repository-code: "https://huggingface.co/DoB24/fundus-9model-benchmark"
+url: "https://huggingface.co/DoB24/fundus-9model-benchmark"
+keywords:
+  - fundus
+  - retinal-imaging
+  - medical-image-classification
+  - deep-learning
+  - benchmark
+  - RETFound
+  - DINOv2
+  - vision-transformer
+abstract: >
+  A reproducible 10-class fundus disease classification benchmark with nine deep
+  models (VGG19, ResNet50, ResNet101, DenseNet121, InceptionV3, Swin-B, CLIP-ViT-B/16,
+  DINOv2-L, RETFound) trained under an identical v2 protocol (CLAHE + RandAugment +
+  WeightedRandomSampler + MixUp/CutMix + 6-view TTA) on a pHash-grouped 5-fold split
+  of the Mendeley 10-class fundus dataset.
+references:
+  - type: dataset
+    title: "Eye disease image dataset"
+    authors:
+      - family-names: Khaled
+        given-names: Mohammad
+    url: "https://data.mendeley.com/datasets/s9bfhswzjb/1"

analysis/confusion_matrices_csv/cm_clip_openai.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],104,0,0,1,0,3,0,0,0,0
+Diabetic Retinopathy,5,687,10,6,0,20,2,0,2,1
+Disc Edema,0,0,137,0,0,0,0,0,0,0
+Glaucoma,2,5,1,389,103,21,85,0,1,2
+Healthy,4,5,0,44,475,8,12,0,0,0
+Macular Scar,3,9,3,10,13,290,4,0,0,2
+Myopia,0,0,0,31,6,11,386,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/confusion_matrices_csv/cm_densenet121.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],101,0,0,1,0,6,0,0,0,0
+Diabetic Retinopathy,5,700,10,4,0,11,1,0,1,1
+Disc Edema,0,0,137,0,0,0,0,0,0,0
+Glaucoma,2,4,1,494,55,12,39,0,0,2
+Healthy,3,0,0,55,467,11,12,0,0,0
+Macular Scar,2,1,3,14,5,303,4,0,0,2
+Myopia,0,3,0,34,9,9,379,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/confusion_matrices_csv/cm_dinov2_l.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],102,0,0,0,0,6,0,0,0,0
+Diabetic Retinopathy,5,707,5,4,0,10,0,0,1,1
+Disc Edema,0,0,136,0,0,1,0,0,0,0
+Glaucoma,2,5,1,487,68,12,31,0,1,2
+Healthy,3,0,0,40,487,10,8,0,0,0
+Macular Scar,2,4,3,13,2,303,5,0,0,2
+Myopia,0,5,0,51,22,6,350,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/confusion_matrices_csv/cm_inception_v3.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],102,0,0,0,0,6,0,0,0,0
+Diabetic Retinopathy,5,701,10,4,0,10,1,0,1,1
+Disc Edema,0,0,137,0,0,0,0,0,0,0
+Glaucoma,2,6,1,492,60,11,35,0,0,2
+Healthy,3,0,0,59,463,13,10,0,0,0
+Macular Scar,2,3,3,12,2,304,6,0,0,2
+Myopia,0,4,0,47,12,7,364,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/confusion_matrices_csv/cm_resnet101.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],102,0,0,1,0,5,0,0,0,0
+Diabetic Retinopathy,5,702,6,5,0,11,2,0,1,1
+Disc Edema,0,1,136,0,0,0,0,0,0,0
+Glaucoma,2,6,1,478,69,15,36,0,0,2
+Healthy,3,0,0,53,473,9,10,0,0,0
+Macular Scar,2,6,3,13,2,303,3,0,0,2
+Myopia,0,4,0,34,16,10,370,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/confusion_matrices_csv/cm_resnet50.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],102,0,0,0,0,6,0,0,0,0
+Diabetic Retinopathy,5,699,10,5,0,11,1,0,1,1
+Disc Edema,0,1,136,0,0,0,0,0,0,0
+Glaucoma,2,6,1,486,70,12,30,0,0,2
+Healthy,3,0,0,50,475,10,10,0,0,0
+Macular Scar,2,3,3,15,5,299,5,0,0,2
+Myopia,0,3,0,52,10,7,362,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/confusion_matrices_csv/cm_retfound.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],101,0,0,1,0,6,0,0,0,0
+Diabetic Retinopathy,5,688,13,5,0,18,2,0,1,1
+Disc Edema,0,4,132,0,0,0,1,0,0,0
+Glaucoma,3,6,1,410,77,26,82,0,2,2
+Healthy,7,4,2,82,426,6,21,0,0,0
+Macular Scar,11,6,4,11,16,268,14,0,1,3
+Myopia,0,0,0,56,7,4,367,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/confusion_matrices_csv/cm_swin_b.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],103,0,0,0,0,5,0,0,0,0
+Diabetic Retinopathy,5,698,10,5,0,10,3,0,1,1
+Disc Edema,0,0,137,0,0,0,0,0,0,0
+Glaucoma,2,5,1,454,85,15,44,0,1,2
+Healthy,5,4,0,66,458,4,11,0,0,0
+Macular Scar,4,4,3,14,6,291,10,0,0,2
+Myopia,0,0,0,73,15,0,346,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/confusion_matrices_csv/cm_vgg19.csv

@@ -0,0 +1,11 @@
+,Central Serous Chorioretinopathy [Color Fundus],Diabetic Retinopathy,Disc Edema,Glaucoma,Healthy,Macular Scar,Myopia,Pterygium,Retinal Detachment,Retinitis Pigmentosa
+Central Serous Chorioretinopathy [Color Fundus],105,0,0,1,0,2,0,0,0,0
+Diabetic Retinopathy,5,698,10,6,0,10,2,0,1,1
+Disc Edema,0,0,137,0,0,0,0,0,0,0
+Glaucoma,2,3,1,470,76,16,39,0,0,2
+Healthy,3,0,0,51,473,9,12,0,0,0
+Macular Scar,3,4,3,13,6,298,5,0,0,2
+Myopia,0,0,0,30,12,7,385,0,0,6
+Pterygium,0,0,0,0,0,0,0,17,0,0
+Retinal Detachment,0,0,0,0,0,0,0,0,127,0
+Retinitis Pigmentosa,0,0,0,0,0,0,0,0,0,155

analysis/per_class_metrics.csv

@@ -0,0 +1,91 @@
+model,class,precision,recall,f1,support
+vgg19,Central Serous Chorioretinopathy [Color Fundus],0.8898,0.9722,0.9292,108
+vgg19,Diabetic Retinopathy,0.9901,0.9523,0.9708,733
+vgg19,Disc Edema,0.9073,1.0000,0.9514,137
+vgg19,Glaucoma,0.8231,0.7718,0.7966,609
+vgg19,Healthy,0.8342,0.8631,0.8484,548
+vgg19,Macular Scar,0.8713,0.8922,0.8817,334
+vgg19,Myopia,0.8691,0.8750,0.8720,440
+vgg19,Pterygium,1.0000,1.0000,1.0000,17
+vgg19,Retinal Detachment,0.9922,1.0000,0.9961,127
+vgg19,Retinitis Pigmentosa,0.9337,1.0000,0.9657,155
+resnet50,Central Serous Chorioretinopathy [Color Fundus],0.8947,0.9444,0.9189,108
+resnet50,Diabetic Retinopathy,0.9817,0.9536,0.9675,733
+resnet50,Disc Edema,0.9067,0.9927,0.9477,137
+resnet50,Glaucoma,0.7993,0.7980,0.7987,609
+resnet50,Healthy,0.8482,0.8668,0.8574,548
+resnet50,Macular Scar,0.8667,0.8952,0.8807,334
+resnet50,Myopia,0.8873,0.8227,0.8538,440
+resnet50,Pterygium,1.0000,1.0000,1.0000,17
+resnet50,Retinal Detachment,0.9922,1.0000,0.9961,127
+resnet50,Retinitis Pigmentosa,0.9337,1.0000,0.9657,155
+resnet101,Central Serous Chorioretinopathy [Color Fundus],0.8947,0.9444,0.9189,108
+resnet101,Diabetic Retinopathy,0.9764,0.9577,0.9669,733
+resnet101,Disc Edema,0.9315,0.9927,0.9611,137
+resnet101,Glaucoma,0.8185,0.7849,0.8013,609
+resnet101,Healthy,0.8446,0.8631,0.8538,548
+resnet101,Macular Scar,0.8584,0.9072,0.8821,334
+resnet101,Myopia,0.8789,0.8409,0.8595,440
+resnet101,Pterygium,1.0000,1.0000,1.0000,17
+resnet101,Retinal Detachment,0.9922,1.0000,0.9961,127
+resnet101,Retinitis Pigmentosa,0.9337,1.0000,0.9657,155
+densenet121,Central Serous Chorioretinopathy [Color Fundus],0.8938,0.9352,0.9140,108
+densenet121,Diabetic Retinopathy,0.9887,0.9550,0.9715,733
+densenet121,Disc Edema,0.9073,1.0000,0.9514,137
+densenet121,Glaucoma,0.8206,0.8112,0.8159,609
+densenet121,Healthy,0.8713,0.8522,0.8616,548
+densenet121,Macular Scar,0.8608,0.9072,0.8834,334
+densenet121,Myopia,0.8713,0.8614,0.8663,440
+densenet121,Pterygium,1.0000,1.0000,1.0000,17
+densenet121,Retinal Detachment,0.9922,1.0000,0.9961,127
+densenet121,Retinitis Pigmentosa,0.9337,1.0000,0.9657,155
+inception_v3,Central Serous Chorioretinopathy [Color Fundus],0.8947,0.9444,0.9189,108
+inception_v3,Diabetic Retinopathy,0.9818,0.9563,0.9689,733
+inception_v3,Disc Edema,0.9073,1.0000,0.9514,137
+inception_v3,Glaucoma,0.8013,0.8079,0.8046,609
+inception_v3,Healthy,0.8622,0.8449,0.8535,548
+inception_v3,Macular Scar,0.8661,0.9102,0.8876,334
+inception_v3,Myopia,0.8750,0.8273,0.8505,440
+inception_v3,Pterygium,1.0000,1.0000,1.0000,17
+inception_v3,Retinal Detachment,0.9922,1.0000,0.9961,127
+inception_v3,Retinitis Pigmentosa,0.9337,1.0000,0.9657,155
+swin_b,Central Serous Chorioretinopathy [Color Fundus],0.8655,0.9537,0.9075,108
+swin_b,Diabetic Retinopathy,0.9817,0.9523,0.9668,733
+swin_b,Disc Edema,0.9073,1.0000,0.9514,137
+swin_b,Glaucoma,0.7418,0.7455,0.7437,609
+swin_b,Healthy,0.8121,0.8358,0.8237,548
+swin_b,Macular Scar,0.8954,0.8713,0.8832,334
+swin_b,Myopia,0.8357,0.7864,0.8103,440
+swin_b,Pterygium,1.0000,1.0000,1.0000,17
+swin_b,Retinal Detachment,0.9845,1.0000,0.9922,127
+swin_b,Retinitis Pigmentosa,0.9337,1.0000,0.9657,155
+clip_openai,Central Serous Chorioretinopathy [Color Fundus],0.8814,0.9630,0.9204,108
+clip_openai,Diabetic Retinopathy,0.9731,0.9372,0.9548,733
+clip_openai,Disc Edema,0.9073,1.0000,0.9514,137
+clip_openai,Glaucoma,0.8087,0.6388,0.7138,609
+clip_openai,Healthy,0.7956,0.8668,0.8297,548
+clip_openai,Macular Scar,0.8215,0.8683,0.8443,334
+clip_openai,Myopia,0.7894,0.8773,0.8310,440
+clip_openai,Pterygium,1.0000,1.0000,1.0000,17
+clip_openai,Retinal Detachment,0.9769,1.0000,0.9883,127
+clip_openai,Retinitis Pigmentosa,0.9337,1.0000,0.9657,155
+dinov2_l,Central Serous Chorioretinopathy [Color Fundus],0.8947,0.9444,0.9189,108
+dinov2_l,Diabetic Retinopathy,0.9806,0.9645,0.9725,733
+dinov2_l,Disc Edema,0.9379,0.9927,0.9645,137
+dinov2_l,Glaucoma,0.8185,0.7997,0.8090,609
+dinov2_l,Healthy,0.8411,0.8887,0.8642,548
+dinov2_l,Macular Scar,0.8707,0.9072,0.8886,334
+dinov2_l,Myopia,0.8883,0.7955,0.8393,440
+dinov2_l,Pterygium,1.0000,1.0000,1.0000,17
+dinov2_l,Retinal Detachment,0.9845,1.0000,0.9922,127
+dinov2_l,Retinitis Pigmentosa,0.9337,1.0000,0.9657,155
+retfound,Central Serous Chorioretinopathy [Color Fundus],0.7953,0.9352,0.8596,108
+retfound,Diabetic Retinopathy,0.9718,0.9386,0.9549,733
+retfound,Disc Edema,0.8684,0.9635,0.9135,137
+retfound,Glaucoma,0.7257,0.6732,0.6985,609
+retfound,Healthy,0.8099,0.7774,0.7933,548
+retfound,Macular Scar,0.8171,0.8024,0.8097,334
+retfound,Myopia,0.7536,0.8341,0.7918,440
+retfound,Pterygium,1.0000,1.0000,1.0000,17
+retfound,Retinal Detachment,0.9695,1.0000,0.9845,127
+retfound,Retinitis Pigmentosa,0.9281,1.0000,0.9627,155

code/hparams.json

@@ -0,0 +1,85 @@
+{
+  "common": {
+    "image_size": 224,
+    "batch_size": 32,
+    "optimizer": "AdamW",
+    "weight_decay": 0.0001,
+    "lr_schedule": "warmup-cosine",
+    "warmup_epochs": 3,
+    "total_epochs": 60,
+    "early_stopping_patience": 12,
+    "label_smoothing": 0.1,
+    "loss": "CrossEntropyLoss (label-smoothed)",
+    "mixup_alpha": 0.2,
+    "cutmix_alpha": 1.0,
+    "mixup_cutmix_prob": 0.7,
+    "sampler": "WeightedRandomSampler (inverse-frequency)",
+    "augmentations": [
+      "CLAHE (cliplimit=2.0, tilegrid=8x8)",
+      "RandAugment (n=2, m=9)",
+      "RandomHorizontalFlip(0.5)",
+      "RandomVerticalFlip(0.2)",
+      "ColorJitter(brightness=0.2, contrast=0.2, saturation=0.2)",
+      "RandomErasing(p=0.25)",
+      "Normalize(ImageNet stats)"
+    ],
+    "tta": {
+      "crops": 6,
+      "ops": [
+        "centre",
+        "horizontal-flip",
+        "vertical-flip",
+        "rot90",
+        "rot180",
+        "rot270"
+      ]
+    },
+    "amp": "fp16",
+    "split": "Group-aware StratifiedGroupKFold(5) on pHash groups, fold 0 = test"
+  },
+  "per_model_learning_rate": {
+    "vgg19": 0.0001,
+    "resnet50": 0.0001,
+    "resnet101": 0.0001,
+    "densenet121": 0.0001,
+    "inception_v3": 0.0001,
+    "swin_b": 5e-05,
+    "clip_openai": 5e-05,
+    "dinov2_l": {
+      "stage1_head_only_lr": 0.001,
+      "stage1_epochs": 20,
+      "stage2_full_lr": 1e-05,
+      "stage2_epochs": 40
+    },
+    "retfound": {
+      "stage1_head_only_lr": 0.001,
+      "stage1_epochs": 20,
+      "stage2_full_lr": 1e-05,
+      "stage2_epochs": 40
+    }
+  },
+  "ensemble": {
+    "method": "soft-vote",
+    "weights": "per-model validation F1, L1-normalised",
+    "calibration": "per-model temperature scaling on validation set",
+    "conformal": "Mondrian (class-conditioned) split-conformal at 90% coverage"
+  },
+  "hardware": {
+    "gpu": "NVIDIA Tesla T4 (16 GB)",
+    "cuda": "12.8",
+    "pytorch": "2.11.0+cu128",
+    "approx_gpu_hours": {
+      "vgg19": 2.5,
+      "resnet50": 2.3,
+      "resnet101": 3.1,
+      "densenet121": 2.8,
+      "inception_v3": 2.2,
+      "swin_b": 4.5,
+      "clip_openai": 3.8,
+      "dinov2_l": 11.2,
+      "retfound": 9.4,
+      "ensemble_and_stats": 0.3,
+      "total": 42.1
+    }
+  }
+}

code/inference_example.py

@@ -0,0 +1,85 @@
+"""Minimal inference example for DoB24/fundus-9model-benchmark.
+
+Loads one of the 9 trained checkpoints, applies the same preprocessing used
+during evaluation, and predicts a class for a single fundus image.
+
+Usage:
+    python inference_example.py path/to/image.jpg --model densenet121
+"""
+from __future__ import annotations
+import argparse, json
+from pathlib import Path
+import torch
+import torch.nn.functional as F
+from torchvision import transforms
+from PIL import Image
+import timm
+from huggingface_hub import hf_hub_download
+
+REPO = "DoB24/fundus-9model-benchmark"
+CLASSES = [
+    "Central Serous Chorioretinopathy",
+    "Diabetic Retinopathy", "Disc Edema", "Glaucoma", "Healthy",
+    "Macular Scar", "Myopia", "Pterygium",
+    "Retinal Detachment", "Retinitis Pigmentosa",
+]
+# Map repo-name to timm model id
+TIMM_ID = {
+    "vgg19": "vgg19", "resnet50": "resnet50", "resnet101": "resnet101",
+    "densenet121": "densenet121", "inception_v3": "inception_v3",
+    "swin_b": "swin_base_patch4_window7_224",
+}
+
+def load_model(name: str, num_classes: int = 10):
+    weights = hf_hub_download(REPO, f"weights/{name}_best.pth")
+    if name in TIMM_ID:
+        model = timm.create_model(TIMM_ID[name], pretrained=False, num_classes=num_classes)
+        if name == "inception_v3":
+            model = timm.create_model("inception_v3", pretrained=False,
+                                      num_classes=num_classes, aux_logits=False)
+    elif name == "clip_openai":
+        import open_clip
+        model, _, _ = open_clip.create_model_and_transforms("ViT-B-16", pretrained=None)
+        model.visual.proj = None
+        model = torch.nn.Sequential(model.visual, torch.nn.Linear(768, num_classes))
+    elif name == "dinov2_l":
+        model = torch.hub.load("facebookresearch/dinov2", "dinov2_vitl14")
+        model = torch.nn.Sequential(model, torch.nn.Linear(1024, num_classes))
+    elif name == "retfound":
+        model = timm.create_model("vit_large_patch16_224", pretrained=False,
+                                  num_classes=num_classes)
+    else:
+        raise ValueError(f"Unknown model: {name}")
+    sd = torch.load(weights, map_location="cpu", weights_only=False)
+    if isinstance(sd, dict) and "state_dict" in sd:
+        sd = sd["state_dict"]
+    model.load_state_dict(sd, strict=False)
+    model.eval()
+    return model
+
+def preprocess(img_path: str) -> torch.Tensor:
+    tf = transforms.Compose([
+        transforms.Resize((224, 224)),
+        transforms.ToTensor(),
+        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
+    ])
+    return tf(Image.open(img_path).convert("RGB")).unsqueeze(0)
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("image")
+    ap.add_argument("--model", default="densenet121",
+                    choices=list(TIMM_ID) + ["clip_openai", "dinov2_l", "retfound"])
+    args = ap.parse_args()
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model = load_model(args.model).to(device)
+    x = preprocess(args.image).to(device)
+    with torch.no_grad():
+        probs = F.softmax(model(x), dim=1)[0].cpu().numpy()
+    order = probs.argsort()[::-1]
+    print(f"\nTop-3 predictions for {args.image} using {args.model}:")
+    for i in order[:3]:
+        print(f"  {CLASSES[i]:40s}  {probs[i]*100:5.2f} %")
+
+if __name__ == "__main__":
+    main()

dataset/README.md

@@ -0,0 +1,20 @@
+# Dataset Figures
+
+- `class_distribution.png` — bar chart of per-class counts (original vs augmented)
+- `class_distribution.csv` — raw counts (machine-readable)
+- `sample_grid.png` — one representative image per class (Original Dataset, seed=42)
+
+## Class counts
+| Class | Original | Augmented |
+|---|---:|---:|
+| Central Serous Chorioretinopathy [Color Fundus] | 101 | 606 |
+| Diabetic Retinopathy | 1509 | 3444 |
+| Disc Edema | 127 | 762 |
+| Glaucoma | 1349 | 2880 |
+| Healthy | 1024 | 2676 |
+| Macular Scar | 444 | 1937 |
+| Myopia | 500 | 2251 |
+| Pterygium | 17 | 102 |
+| Retinal Detachment | 125 | 750 |
+| Retinitis Pigmentosa | 139 | 834 |
+| **TOTAL** | **5335** | **16242** |

dataset/class_distribution.csv

@@ -0,0 +1,12 @@
+class,augmented_count,original_count
+Central Serous Chorioretinopathy [Color Fundus],606,101
+Diabetic Retinopathy,3444,1509
+Disc Edema,762,127
+Glaucoma,2880,1349
+Healthy,2676,1024
+Macular Scar,1937,444
+Myopia,2251,500
+Pterygium,102,17
+Retinal Detachment,750,125
+Retinitis Pigmentosa,834,139
+TOTAL,16242,5335