| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Lower |
| '1': Upper |
| splits: |
| - name: original |
| num_bytes: 2575827.0 |
| num_examples: 32 |
| - name: augmented |
| num_bytes: 22191126.0 |
| num_examples: 320 |
| download_size: 24632318 |
| dataset_size: 24766953.0 |
| configs: |
| - config_name: default |
| data_files: |
| - split: original |
| path: data/original-* |
| - split: augmented |
| path: data/augmented-* |
| --- |
| |
| # Gym Machines Image Dataset |
|
|
| ## Dataset Summary |
| This dataset includes **30+ original, student-created images** of gym machines (objects and small arrangements/scenes) with a **binary classification target** for each image: |
| - `0 = Lower body machine` |
| - `1 = Upper body machine` |
|
|
| The dataset is stored on Hugging Face with two splits: |
| - **original**: 32 manually collected and labeled images |
| - **augmented**: 320 synthetic samples generated via label-preserving transformations |
|
|
| Total: **350+ images** |
|
|
| --- |
|
|
| ## Purpose |
| This dataset was created as part of a course assignment to demonstrate: |
| - Safe collection of original image data |
| - Application of augmentation techniques for dataset expansion |
| - Preparation and publishing of datasets to Hugging Face for reproducibility and sharing |
|
|
| It is intended for **educational use** in computer vision, data preprocessing, and augmentation workflows. |
|
|
| --- |
|
|
| ## Composition |
| - **Subjects**: Common gym machines (e.g., leg press, hack squat, chest press, lat pulldown). |
| - **Labels**: Binary (`Lower`, `Upper`). |
| - **Images**: 224×224 RGB, `.jpg` format. |
| - **Counts**: |
| - Original split: 32 images |
| - Augmented split: 320 images |
|
|
| --- |
|
|
| ## Data Collection |
| - Images were captured safely by the student, without any people or personally identifiable information (PII). |
| - Only objects and gym machines were included. |
| - All images were resized to **224×224 pixels**. |
|
|
| --- |
|
|
| ## Preprocessing & Augmentation |
| ### Preprocessing |
| - Converted to RGB |
| - Resized to **224×224** |
|
|
| ### Augmentation Techniques |
| Applied using PyTorch/TorchVision: |
| - Random horizontal flip (p=0.5) |
| - Random rotation (±20°) |
| - Random color jitter (brightness, contrast, saturation ±0.3) |
| - Random resized crop (scale = 0.8–1.0) |
| - Gaussian blur |
|
|
| These transformations expanded the dataset from 32 originals to 320 augmented samples, while preserving labels. |
|
|
| --- |
|
|
| ## Labels |
| - **Binary target**: |
| - `0` → Lower body machine |
| - `1` → Upper body machine |
|
|
| Labels were manually assigned by the student based on machine function. |
|
|
| --- |
|
|
| ## Splits |
| - **original** → 32 images |
| - **augmented** → 320 images |
| - Published as a `DatasetDict` on Hugging Face. |
|
|
| --- |
|
|
| ## Intended Use & Limitations |
| - **Use cases**: Educational exercises in dataset handling, preprocessing, augmentation, and Hugging Face dataset publishing. |
| - **Not intended for**: Medical, health, or workout guidance. |
| - **Limitations**: |
| - Small dataset size → not suitable for production training |
| - Labels are simplified (`Upper` vs `Lower`) and may not capture full machine usage |
|
|
| --- |
|
|
| ## Ethical Considerations |
| - No people or personal information were included. |
| - No sensitive content. |
| - Strictly object-based dataset. |
|
|
| --- |
|
|
| ## License |
| - Released under **CC BY-NC-SA 4.0** (Attribution–NonCommercial–ShareAlike). |
| - You may use and adapt for educational/research purposes with attribution. |
| - Not for commercial use. |
|
|
| --- |
|
|
| ## AI Usage Disclosure |
| - AI tools (e.g., ChatGPT) assisted in: |
| - Structuring the dataset card |
| - All images were **student-created**, not AI-generated. |
|
|
