--- dataset_info: features: - name: image dtype: image - name: task dtype: string - name: label dtype: string - name: description dtype: string - name: dataset_type dtype: string - name: question dtype: string - name: options list: string - name: shape dtype: string - name: color dtype: string - name: size_class dtype: string - name: location dtype: string - name: angle dtype: string splits: - name: angle num_bytes: 375221 num_examples: 240 - name: angle_count num_bytes: 156342 num_examples: 100 - name: color num_bytes: 375221 num_examples: 240 - name: color_count num_bytes: 156342 num_examples: 100 - name: count num_bytes: 156342 num_examples: 100 - name: location num_bytes: 375221 num_examples: 240 - name: location_count num_bytes: 156342 num_examples: 100 - name: occlusion num_bytes: 156342 num_examples: 100 - name: position num_bytes: 156342 num_examples: 100 - name: shape num_bytes: 375221 num_examples: 240 - name: shape_count num_bytes: 156342 num_examples: 100 - name: size num_bytes: 375221 num_examples: 240 - name: size_count num_bytes: 156342 num_examples: 100 - name: train num_bytes: 3128593 num_examples: 2000 download_size: 3659488 dataset_size: 6255434 configs: - config_name: default data_files: - split: angle path: data/angle-* - split: angle_count path: data/angle_count-* - split: color path: data/color-* - split: color_count path: data/color_count-* - split: count path: data/count-* - split: location path: data/location-* - split: location_count path: data/location_count-* - split: occlusion path: data/occlusion-* - split: position path: data/position-* - split: shape path: data/shape-* - split: shape_count path: data/shape_count-* - split: size path: data/size-* - split: size_count path: data/size_count-* - split: train path: data/train-* --- ## Dataset Description This dataset contains two types of tasks: ### Single-Object Tasks (5 tasks, 1,200 samples) - **Shape**: Identify object shape (star, diamond, triangle, square) - **Color**: Identify object color (red, green, blue, yellow) - **Size**: Identify object size (xs, s, l, xl) - **Location**: Identify object location (upper_left, upper_right, lower_left, lower_right) - **Angle**: Identify triangle orientation (0°, 45°, 90°, 135°) ### Multi-Object Tasks (3 tasks, 300 samples) - **Count**: Count objects by color - **Position**: Determine relative position (left, right, above, below) - **Occlusion**: Identify which object is on top ## Key Features - **White background** for clarity - **Randomized attributes**: Each task randomizes non-target attributes to prevent shortcuts - **Description field**: Enables text-only experiments (image vs. text-only comparison) - **Balanced classes**: Equal samples per class within each task ## Dataset Structure ```python { "image": PIL.Image, "task": str, # Task name "label": str, # Ground truth label "description": str, # Text description of the image "dataset_type": str, # "single" or "multi" "question": str, # Question text (multi-object only) "options": List[str], # Answer options (multi-object only) "shape": str, # Object shape (if applicable) "color": str, # Object color (if applicable) "size_class": str, # Size class (if applicable) "location": str, # Location (if applicable) "angle": str, # Angle (if applicable) } ``` ## Usage ```python from datasets import load_dataset # Load entire dataset ds = load_dataset("Hanoi0126/visual-object-attributes") # Load specific task ds_color = load_dataset("Hanoi0126/visual-object-attributes", split="color") ```