Blood_5_for_classification

# Datasets

## 1. Classification WBC — Blood5 (Self-Collected)

### Overview

Blood5 is a **self-collected peripheral white blood cell (WBC) microscopy dataset** for five-class classification. It covers all five major mature leukocyte subtypes seen in clinical hematology: basophil, eosinophil, lymphocyte, monocyte, and neutrophil.

### Scale

| Split | Samples |
|——-|——–:|
| Train | 20,697 |
| Test  | 5,175 |
| **Total** | **25,872** |

### Class Distribution

| Index | Class | Train | Proportion |
|:—–:|——-|——:|———–:|
| 0 | Basophil | 424 | 2.0% |
| 1 | Eosinophil | 472 | 2.3% |
| 2 | Lymphocyte | 3,969 | 19.2% |
| 3 | Monocyte | 2,054 | 9.9% |
| 4 | Neutrophil | 9,638 | 46.6% |

> The dataset exhibits **severe natural class imbalance** — neutrophils dominate while basophils and eosinophils are rare (<5% combined) — faithfully reflecting real-world clinical prevalence.

### Collection & Preprocessing

1. Blood smears prepared and stained following standard hematology protocols.
2. Images captured via optical microscope with digital camera.
3. Converted to RGB and resized to **150×150** pixels.
4. Stored in CIFAR-10 binary pickle format with 80:20 stratified split (random seed = 42).
5. Online augmentations: `RandomResizedCrop` (224×224), `RandAugment`, `Cutout`.

### File Format

| File | Content |
|——|———|
| `batches.meta` | Label name mapping |
| `data_batch_1` | Train batch 1 (10,000) |
| `data_batch_2` | Train batch 2 (10,000) |
| `data_batch_3` | Train batch 3 (697) |
| `test_batch` | Test set (5,175) |

Each image: flattened 1D array (150×150×3 = 67,500 elements) → reshaped to H×W×C on load.

### Subset: Blood3

A three-class subset (lymphocyte, monocyte, neutrophil) is also provided for fast prototyping.

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## 2. Segmentation WBC (Public)

### Overview

Two publicly available WBC **segmentation** datasets from Zheng et al. (2018), used for evaluating cell segmentation methods. These datasets differ substantially in color, cell morphology, and background — offering a robust test of generalization.

### Ground Truth

Masks are manually annotated by domain experts with three regions:

| Intensity | Region |
|:———:|——–|
| White | Nucleus |
| Gray | Cytoplasm |
| Black | Background (incl. red blood cells) |

### Dataset 1

| Property | Value |
|———-|——-|
| Source | Jiangxi Tecom Science Corp., China |
| Samples | 300 |
| Resolution | 120×120 |
| Color depth | 24-bit |
| Microscope | Motic Moticam Pro 252A + N800-D autofocus |
| Staining | Novel rapid hematology reagent |
| Appearance | Yellowish background |

### Dataset 2

| Property | Value |
|