Datasets:

siddharthhf1709
/

indian_food_dataset

Error code:   DatasetGenerationError
Exception:    IndexError
Message:      list index out of range
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1811, in _prepare_split_single
                  original_shard_lengths[original_shard_id] += len(table)
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
              IndexError: list index out of range
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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End of preview.

Indian Food Dataset

This dataset is designed for object detection of various Indian food items. It follows the YOLO format and includes 20 different classes of food and drinks.

Dataset Structure

images/: Contains training and validation images.
labels/: Contains YOLO format label files (.txt).
data.yaml: Configuration file defining classes and paths.

Classes

The dataset contains the following 20 classes:

Chicken_Curry
Plain_Omelette
Spinach_Paneer
Appam
Avial
Banana_Chips
Chapati_Roti
Chocolate_Cake
Fruit_Salad
Idli
Kulfi
Marble_Cake
Masala_Dosa
Masala_Vada
Mutton_Biryani
Pancake
Sambar
Uttapam
Lemonade
Rice_Puttu

Usage

This dataset can be used to train object detection models like YOLOv8, YOLOv9, or YOLOv10.

Training with Ultralytics YOLOv8

from ultralytics import YOLO

# Load a model
model = YOLO('yolov8n.pt')

# Train the model
results = model.train(data='data.yaml', epochs=100, imgsz=640)

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Total file size:

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