| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: image_id |
| dtype: int64 |
| - name: file_name |
| dtype: string |
| - name: width |
| dtype: int64 |
| - name: height |
| dtype: int64 |
| - name: camera_height_img |
| dtype: int64 |
| - name: objects |
| struct: |
| - name: annotation_id |
| list: int64 |
| - name: area |
| list: float64 |
| - name: bbox |
| list: |
| list: float64 |
| - name: camera_height_ann |
| list: int64 |
| - name: category_id |
| list: int64 |
| - name: difficult |
| list: int64 |
| - name: ignore |
| list: int64 |
| - name: person_location |
| list: |
| list: float64 |
| - name: ritbox |
| list: |
| list: float64 |
| - name: rotated_box |
| list: |
| list: float64 |
| - name: segmentation |
| list: |
| list: float64 |
| - name: world_location |
| list: |
| list: float64 |
| splits: |
| - name: train |
| num_bytes: 2908124774.58 |
| num_examples: 29569 |
| - name: validation |
| num_bytes: 557308312.6 |
| num_examples: 4600 |
| - name: test |
| num_bytes: 1173421936.14 |
| num_examples: 8773 |
| download_size: 4870084026 |
| dataset_size: 4638855023.32 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: validation |
| path: data/validation-* |
| - split: test |
| path: data/test-* |
| --- |
| |
| ```python |
| from datasets import load_dataset |
| import matplotlib.pyplot as plt |
| import matplotlib.patches as patches |
| import numpy as np |
| |
| # 1. Load the dataset |
| # Note: Since this is a private repo, ensure you have run `huggingface-cli login` |
| repo_id = "bdanko/loaf_resolution_512" |
| print(f"Downloading {repo_id}...") |
| dataset = load_dataset(repo_id, split="train") |
| |
| # 2. Grab the first example |
| example = dataset[0] |
| |
| # Hugging Face automatically decodes the Parquet bytes into a PIL Image |
| img = example["image"] |
| objects = example["objects"] |
| |
| # Print image-level metadata |
| print("\n--- Image Metadata ---") |
| print(f"File Name: {example['file_name']}") |
| print(f"Image ID: {example['image_id']}") |
| print(f"Dimensions: {example['width']}x{example['height']}") |
| print(f"Camera Height (Image): {example['camera_height_img']}") |
| |
| # 3. Set up the matplotlib plot |
| fig, ax = plt.subplots(1, figsize=(10, 8)) |
| ax.imshow(img) |
| ax.axis("off") |
| ax.set_title(f"Sample: {example['file_name']}", fontsize=14) |
| |
| print("\n--- Object Metadata ---") |
| |
| # 4. Iterate through all objects in this image |
| # We use zip to unpack all the parallel lists stored inside the 'objects' dictionary |
| num_objects = len(objects["annotation_id"]) |
| |
| for i in range(num_objects): |
| ann_id = objects["annotation_id"][i] |
| cat_id = objects["category_id"][i] |
| bbox = objects["bbox"][i] |
| seg = objects["segmentation"][i] |
| |
| # Custom / 3D annotations |
| ritbox = objects["ritbox"][i] |
| rot_box = objects["rotated_box"][i] |
| world_loc = objects["world_location"][i] |
| person_loc = objects["person_location"][i] |
| cam_height_ann = objects["camera_height_ann"][i] |
| |
| print(f"\nObject {i+1} (Ann ID: {ann_id} | Category: {cat_id})") |
| print(f" - 2D BBox: {bbox}") |
| print(f" - Ritbox: {ritbox}") |
| print(f" - Rotated Box: {rot_box}") |
| print(f" - World Location: {world_loc}") |
| print(f" - Person Location: {person_loc}") |
| print(f" - Camera Height: {cam_height_ann}") |
| |
| # --- Plotting the 2D Bounding Box --- |
| # COCO bbox format is [top_left_x, top_left_y, width, height] |
| if len(bbox) == 4: |
| x, y, w, h = bbox |
| rect = patches.Rectangle( |
| (x, y), w, h, |
| linewidth=2, edgecolor='red', facecolor='none', label=f"Cat {cat_id}" |
| ) |
| ax.add_patch(rect) |
| ax.text(x, y - 5, f"Cat {cat_id}", color='red', fontsize=10, weight='bold') |
| |
| # --- Plotting the Segmentation Polygon --- |
| # COCO segmentation is a flat list: [x1, y1, x2, y2, ...] |
| if len(seg) > 0: |
| # Reshape flat list into a list of (x, y) coordinate pairs |
| poly_coords = np.array(seg).reshape(-1, 2) |
| polygon = patches.Polygon( |
| poly_coords, |
| linewidth=2, edgecolor='cyan', facecolor='cyan', alpha=0.3 |
| ) |
| ax.add_patch(polygon) |
| |
| plt.tight_layout() |
| plt.show() |
| ``` |
|
|
|
|
|  |
