Upload folder using huggingface_hub

.gitattributes

@@ -57,3 +57,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+train/labels.cache filter=lfs diff=lfs merge=lfs -text

README.dataset.txt

@@ -0,0 +1,17 @@
+# Pool Balls Detection > 2025-10-21 11:59pm
+https://universe.roboflow.com/nhan-wzcb7/pool-balls-detection-srlqi-iqsqo
+
+Provided by a Roboflow user
+License: CC BY 4.0
+
+Here are a few use cases for this project:
+
+1. **Pool Game Assistant**: This computer vision model can be used for building an augmented reality app that assists pool players in taking shots. By detecting the balls and their numbers, the app could suggest optimal shot angles and strategies for the game.
+
+2. **Sport Broadcast Enhancement**: The Pool Balls Detection model can be incorporated into broadcasting technologies for professional sports. Through identifying each ball, it can provide real-time graphics showcasing the ball statistics such as remaining balls, a particular ball's position, or predictive line of shot.
+
+3. **Advanced Training Tool**: This model can be used as part of a virtual coaching app for players seeking to improve their pool game. It can analyze the arrangement of balls and provide feedback on gameplay, or demonstrate how professional players would handle the same scenario.
+
+4. **Billiard Club Management**: The model can be used in a billiard club software to monitor table status. It can detect the game stage based on the balls' positions and identities, helping staff know when a game has ended and the table is ready for the next players.
+
+5. **Efficient Ball Sorter**: For manufactures or pool parlors that need to regularly organize sets of pool balls, this model could be paired with a robotic system to automatically identify and sort different balls, saving time and increasing efficiency.

README.md

@@ -0,0 +1,66 @@
+---
+license: mit
+task_categories:
+- object-detection
+tags:
+- yolo
+- computer-vision
+- pool
+- billiards
+size_categories:
+- n<1K
+---
+
+# Pool Detection Dataset
+
+This is a YOLO format dataset for object detection tasks.
+
+## Dataset Structure
+
+```
+pool/
+  train/
+    images/
+    labels/
+  valid/
+    images/
+    labels/
+  test/
+    images/
+    labels/
+  data.yaml
+```
+
+## Classes
+
+The dataset contains 16 classes representing pool balls (numbered 0-15).
+
+## Usage
+
+### In Python
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("nhantu2107/pool-detection")
+```
+
+### In Kaggle
+
+1. Go to your Kaggle notebook
+2. Click "Add data" -> "Hugging Face"
+3. Search for "pool-detection"
+4. Click "Add"
+
+### With YOLOv8/YOLOv11
+
+```python
+from ultralytics import YOLO
+
+model = YOLO('yolov8n.pt')
+model.train(data='data.yaml', epochs=100)
+```
+
+## Citation
+
+If you use this dataset, please cite appropriately.

README.roboflow.txt

@@ -0,0 +1,28 @@
+
+Pool Balls Detection - v1 2025-10-21 11:59pm
+==============================
+
+This dataset was exported via roboflow.com on October 21, 2025 at 5:00 PM GMT
+
+Roboflow is an end-to-end computer vision platform that helps you
+* collaborate with your team on computer vision projects
+* collect & organize images
+* understand and search unstructured image data
+* annotate, and create datasets
+* export, train, and deploy computer vision models
+* use active learning to improve your dataset over time
+
+For state of the art Computer Vision training notebooks you can use with this dataset,
+visit https://github.com/roboflow/notebooks
+
+To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
+
+The dataset includes 262 images.
+Pool-balls are annotated in YOLOv8 format.
+
+The following pre-processing was applied to each image:
+
+The following augmentation was applied to create 3 versions of each source image:
+* Random brigthness adjustment of between -15 and +15 percent
+
+

UPLOAD_GUIDE.md

@@ -0,0 +1,66 @@
+# Upload Dataset to Hugging Face - Quick Guide
+
+## Step 1: Install Requirements
+
+```bash
+pip install huggingface_hub
+```
+
+## Step 2: Login to Hugging Face
+
+```bash
+huggingface-cli login
+```
+
+You'll need a Hugging Face token:
+1. Go to https://huggingface.co/settings/tokens
+2. Create a new token with "write" permission
+3. Copy and paste it when prompted
+
+## Step 3: Configure the Upload Script
+
+Edit `upload_to_huggingface.py`:
+- Change `HF_USERNAME` to your Hugging Face username
+- Optionally change `DATASET_NAME` to your preferred name
+
+## Step 4: Run the Upload Script
+
+```bash
+python upload_to_huggingface.py
+```
+
+## Step 5: Use in Kaggle
+
+Once uploaded, in your Kaggle notebook:
+
+1. Click "Add Data" button
+2. Select "Hugging Face" tab
+3. Search for your dataset name
+4. Click "Add"
+
+The dataset will be mounted at `/kaggle/input/your-dataset-name/`
+
+## Alternative: Direct Download in Kaggle
+
+If you prefer, you can also download directly in your Kaggle notebook:
+
+```python
+from huggingface_hub import snapshot_download
+
+dataset_path = snapshot_download(
+    repo_id="YOUR_USERNAME/DATASET_NAME",
+    repo_type="dataset",
+    local_dir="./pool_dataset"
+)
+
+print(f"Dataset downloaded to: {dataset_path}")
+```
+
+## Verify Upload
+
+After uploading, visit:
+```
+https://huggingface.co/datasets/YOUR_USERNAME/DATASET_NAME
+```
+
+You should see all your files (train, valid, test folders and data.yaml).

data.yaml

@@ -0,0 +1,7 @@
+path: C:\Users\ADMIN\OneDrive\Desktop\Personal_project\pool
+train: train/images
+val: valid/images
+test: test/images
+
+nc: 16
+names: ['0', '1', '10', '11', '12', '13', '14', '15', '2', '3', '4', '5', '6', '7', '8', '9']

requirements_upload.txt

@@ -0,0 +1 @@
+huggingface_hub

test/labels/z7143458884336_a9ee3db818f4478a53baea567a004186.txt

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test/labels/z7143462884505_bfce87f5d56d7715b8e7c8981c1a9fef.txt

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test/labels/z7143466435453_ae7f81a707877c4bccf1d235f3362fe1.txt

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test/labels/z7143467915149_0b8d3fafd2fa7f7d7057cd1b3040a2fc.txt

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test/labels/z7143469703843_aac1b580794af0b2c08faa0312df5624.txt

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test/labels/z7143470604714_ef7decd96875af06bc0c73bd401d2a7c.txt

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test/labels/z7143471258209_ef8d2a5d39b733bb3f076a27d65038b3.txt

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test/labels/z7143474136046_e2e3c795fbdcbd22d9574ace5eef40b1.txt

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test/labels/z7143476391630_3d24910e40a8489b738f019f1c9a449d.txt

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