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zaheerabbasi
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Hand_Gesture_Recognition_Dataset

Languages:
English
Tags:
computer-vision
image-classification
hand-gesture-recognition
cnn
deep-learning
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Invalid string class label Hand_Gesture_Recognition_Dataset@f9bfd5ad226e5164a907aabb97ad3f1532a87860
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
                  example = _apply_feature_types_on_example(
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2157, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2152, in encode_example
                  return encode_nested_example(self, example)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1437, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1143, in encode_example
                  example_data = self.str2int(example_data)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1080, in str2int
                  output = [self._strval2int(value) for value in values]
                            ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1101, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label Hand_Gesture_Recognition_Dataset@f9bfd5ad226e5164a907aabb97ad3f1532a87860

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Hand Gesture Recognition Dataset for Classroom Control

📝 Description

This dataset is designed for training and evaluating computer vision models for hand gesture recognition. It contains images of different hand gestures that can be used for smart classroom systems, human-computer interaction, and real-time gesture-based control applications.

The dataset is suitable for beginners and intermediate researchers working on convolutional neural networks (CNNs), deep learning, and image classification tasks.

🎯 Purpose

The main goal of this dataset is to enable the development of an AI system that can recognize hand gestures and perform actions such as:

  • Controlling presentation slides
  • Detecting student participation (raise hand)
  • Touchless system interaction
  • Gesture-based commands

🧩 Classes

The dataset contains 5 hand gesture classes:

  • ✋ Stop
  • 👍 Thumbs Up
  • 👎 No
  • 👆 Raise Hand
  • ✌️ OK

📊 Dataset Details

  • Total Images: 500
  • Number of Classes: 5
  • Images per Class: 100
  • Image Type: RGB images

We developed this dataset as part of a hand gesture recognition project focused on smart classroom applications and real-time human-computer interaction.
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