Duplicate from lambdaWalker/creditCardDetectionDS

Co-authored-by: David Garcia <lambdaWalker@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
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+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
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.gitignore

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+weights
+train-log
+*.cache

README.md

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+---
+license: apache-2.0
+task_categories:
+  - object-detection
+pretty_name: Credit Card V0.3 Dataset
+size_categories:
+  - 1K<n<10K
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: images/train/train.jsonl
+      - split: test
+        path: images/test/test.jsonl
+      - split: validation
+        path: images/val/val.jsonl
+tags:
+  - finance
+---
+
+# Synthetic Credit Card Dataset
+
+## Overview
+
+This repository contains a synthetic dataset of credit card images designed for training and validating machine learning models, specifically using the YOLOv8 object detection model. The dataset consists of 3000 items for training and 1000 items for validation and testing. Each image is 800x800 in JPG format and is accompanied by the necessary annotation files for YOLOv8 and Hugging Face.
+
+## Dataset Features
+
+- **Total Items**: 5000
+  - **Training**: 3000 items
+  - **Validation**: 1000 items
+  - **Testing**: 1000 items
+- **Image Format**: JPG
+- **Image Size**: 800x800 pixels
+- **Annotations**: Provided for YOLOv8 and Hugging Face in JSONL format
+
+## Annotations
+
+### YOLOv8
+The annotation files for YOLOv8 are generated as per the [YOLOv8 dataset requirements](https://docs.ultralytics.com/datasets/detect/). Each image has a corresponding `.txt` file with the bounding box coordinates.
+
+### Hugging Face
+The annotation files for Hugging Face are generated in JSONL format as per the [Hugging Face image dataset documentation](https://huggingface.co/docs/datasets/en/image_dataset).
+
+
+## License
+
+This dataset is licensed under the Apache License Version 2.0.
+
+## Contributions
+
+We welcome contributions from the community. If you plan to use this dataset or modified versions in a product, research project, or any other initiative that adds value, please notify us. This helps us maintain a record of users and allows us to acknowledge your contributions on our website.
+
+## Contact
+
+For any inquiries or further information, please contact us at [bytesWright@isdavid.com](mailto:bytesWright@isdavid.com).

card.yaml

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+license: apache-2.0
+task_categories:
+  - object-detection
+pretty_name: Credit Card V0.3 Dataset
+size_categories:
+  - 1K<n<10K
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: /images/train/metadata.jsonl
+      - split: test
+        path: /images/test/metadata.jsonl
+      - split: validation
+        path: /images/val/metadata.jsonl
+tags:
+  - finance

desc.md

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+Train size: 3401
+Val size: 1075
+Test size: 200
+
+Classes:
+    Credit card front face
+    Credit card back face
+    Text (lines)
+    Chip (in front face)
+    Band (in back face)
+
+Training command running from the root of the project:
+    yolo train model=./models/yolov8n.pt data=./datasets/creditCardV0.3/yolo8Config.yaml epochs=300 imgsz=800
+
+Command to export as tflite bellow. For some reason the exception [ModuleNotFoundError: No module named 'tensorflow_lite_support'] is raised but the tflite files are created:
+    yolo export model=./datasets/creditCardV0.3/weights/best.pt format=tflite
+
+Command to test:
+    yolo predict model='./datasets/creditCardV0.3/weights/best.pt' source='./test/T0.jpg'
+    yolo predict model='./datasets/creditCardV0.3/weights/best_float16.tflite' source='./test/T0.jpg'
+    yolo predict model='./datasets/creditCardV0.3/weights/best_float30.tflite' source='./test/T0.jpg'
+
+Notes:
+
+    This data set has an issue with the chip. For some reason it was not generated correctly for some images.
+    The light in the images needs fixing to avoid white clipping parts of the images.
+    The texture of the plastic is too deep some times.
+
+For more info: https://docs.ultralytics.com/