revamped

.gitignore

@@ -0,0 +1,120 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# trial ipynb
+trial.ipynb
+
+# original data
+original_data/

README.md

@@ -48,8 +48,8 @@ task_ids: []
 
 - **Homepage:** https://github.com/faizankshaikh/chessDetection
 - **Repository:** https://github.com/faizankshaikh/chessDetection
-- **Paper:** [Needs More Information]
-- **Leaderboard:** [Needs More Information]
+- **Paper:** -
+- **Leaderboard:** -
 - **Point of Contact:** [Faizan Shaikh](mailto:faizankshaikh@gmail.com)
 
 ### Dataset Summary
@@ -92,7 +92,6 @@ A data point comprises an image and its label.
 
 The data is split into training and validation set. The training set contains 204 images and the validation set 52 images. 
 
-Train Valid 204 52
 
 ## Dataset Creation
 

data/{training-00000-of-00001-4248b21f1fdef089.parquet → train.zip}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:84e6c820dc1a29066401911926430ed61dd4d173524c1341d7c0ab805969f1ff
-size 1238568
+oid sha256:2c0717779d3b83d32ed81bfcdd91468ad9a00135978fde76ed1f4cdb02010ba3
+size 1254072

data/{validation-00000-of-00001-4248b21f1fdef089.parquet → valid.zip}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:84e6c820dc1a29066401911926430ed61dd4d173524c1341d7c0ab805969f1ff
-size 1238568
+oid sha256:438cad2398de0ba6af7f69c208459a65967d45272edd42186cf1bfcf2ecf13be
+size 321278

detect_chess_pieces.py

@@ -0,0 +1,100 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Script for reading 'Object Detection for Chess Pieces' dataset."""
+
+
+import os
+
+import datasets
+
+_CITATION = ""
+
+_DESCRIPTION = """\
+The "Object Detection for Chess Pieces" dataset is a toy dataset created (as suggested by the name!) to introduce object detection in a beginner friendly way.
+"""
+
+_HOMEPAGE = "https://github.com/faizankshaikh/chessDetection"
+
+_LICENSE = "CC-BY-SA:2.0"
+
+_REPO = "data"  # "https://huggingface.co/datasets/jalFaizy/resolve/main/data"
+_URLS = {"train": f"{_REPO}/train.zip", "valid": f"{_REPO}/valid.zip"}
+
+
+class DetectChessPieces(datasets.GeneratorBasedBuilder):
+    """Object Detection for Chess Pieces dataset"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "bboxes": datasets.Sequence(datasets.Value("int32"), length=5),
+                }
+            ),
+            supervised_keys=None,
+            description=_DESCRIPTION,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+            task_templates=[
+                {
+                    "task": "object-detection",
+                    "image_column": "image",
+                    "label_column": "bboxes",
+                }
+            ],
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(_URLS)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"split": "train", "data_dir": data_dir["train"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"split": "valid", "data_dir": data_dir["valid"]},
+            ),
+        ]
+
+    def _generate_examples(self, split, data_dir):
+        image_dir = os.path.join(data_dir, "images")
+        label_dir = os.path.join(data_dir, "labels")
+        for idx, (image_path, label_path) in enumerate(zip(image_dir, label_dir)):
+            im = Image.open(image_path)
+            width, height = im.size
+
+            with open(label_path, "r") as f:
+                lines = f.readlines()
+
+            bboxes = []
+            for line in lines:
+                line = line.strip().split()
+                try:
+                    bbox_class = int(line[0])
+                    bbox_xcenter = int(float(line[1]) * width)
+                    bbox_ycenter = int(float(line[2]) * height)
+                    bbox_width = int(float(line[3]) * width)
+                    bbox_height = int(float(line[4]) * height)
+                except:
+                    print(f"Check file {f.name} for errors")
+
+                bbox = [bbox_class, bbox_xcenter, bbox_ycenter, bbox_width, bbox_height]
+                bboxes.append(bbox)
+
+            yield idx, {"image": image_path, "bboxes": bboxes}