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# 🎥 Computer Vision | ||
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<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(280px, 1fr)); gap: 15px; padding: 10px;"> | ||
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<!-- Face Detection --> | ||
<figure style="padding: 1rem; background: rgba(39, 39, 43, 0.5); border-radius: 10px; border: 1px solid rgba(76, 76, 82, 0.4); box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); transition: transform 0.2s ease-in-out; text-align: center; max-width: 320px; margin: auto;"> | ||
<a href="face-detection" style="color: white; text-decoration: none; display: block;"> | ||
<img src="https://imerit.net/wp-content/uploads/2021/07/Face-Detection-in-Images-with-Bounding-Boxes.jpg" alt="" style="width: 100%; height: 150px; object-fit: cover; border-radius: 8px; transition: transform 0.2s;"> | ||
<div style="padding: 0.8rem;"> | ||
<h3 style="margin: 0; font-size: 18px;">Face Detection Model</h3> | ||
<p style="font-size: 14px; opacity: 0.8;">Detecting faces in images using OpenCV's powerful Haar cascades.</p> | ||
<p style="font-size: 12px; opacity: 0.6;">📅 2025-01-16 | ⏱️ 10 min read</p> | ||
</div> | ||
</a> | ||
</figure> | ||
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<!-- Bicep Reps Counting --> | ||
<figure style="padding: 1rem; background: rgba(39, 39, 43, 0.5); border-radius: 10px; border: 1px solid rgba(76, 76, 82, 0.4); box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); transition: transform 0.2s ease-in-out; text-align: center; max-width: 320px; margin: auto;"> | ||
<a href="bicep-reps-counting" style="color: white; text-decoration: none; display: block;"> | ||
<img src="https://www.researchgate.net/publication/368864097/figure/fig1/AS:11431281123465557@1677717597497/Mediapipe-Poses-position-detection-of-33-posture-joints-Mediapipe-has-many-functions.png" | ||
alt="Bicep Reps Counting" | ||
style="width: 100%; height: 150px; object-fit: cover; border-radius: 8px; transition: transform 0.2s;"> | ||
<div style="padding: 0.8rem;"> | ||
<h3 style="margin: 0; font-size: 18px;">Counting Bicep Reps</h3> | ||
<p style="font-size: 14px; opacity: 0.8;">Real-time tracking and counting of bicep curls with MediaPipe's Pose module and OpenCV.</p> | ||
<p style="font-size: 12px; opacity: 0.6;">📅 2025-01-18 | ⏱️ 15 min read</p> | ||
</div> | ||
</a> | ||
</figure> | ||
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<!-- Brightness Control --> | ||
<figure style="padding: 1rem; background: rgba(39, 39, 43, 0.5); border-radius: 10px; border: 1px solid rgba(76, 76, 82, 0.4); box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); transition: transform 0.2s ease-in-out; text-align: center; max-width: 320px; margin: auto;"> | ||
<a href="brightness-control" style="color: white; text-decoration: none; display: block;"> | ||
<img src="https://user-images.githubusercontent.com/59369441/116009572-1542a280-a638-11eb-9d94-2a2d38b856a5.PNG" | ||
alt="Brightness Control" | ||
style="width: 100%; height: 150px; object-fit: cover; border-radius: 8px; transition: transform 0.2s;"> | ||
<div style="padding: 0.8rem;"> | ||
<h3 style="margin: 0; font-size: 18px;">Brightness Control</h3> | ||
<p style="font-size: 14px; opacity: 0.8;">Adjust screen brightness dynamically using MediaPipe's Hand Tracking and OpenCV.</p> | ||
<p style="font-size: 12px; opacity: 0.6;">📅 2025-01-24 | ⏱️ 10 min read</p> | ||
</div> | ||
</a> | ||
</figure> | ||
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<!-- Black and White Image Colorizer --> | ||
<figure style="padding: 1rem; background: rgba(39, 39, 43, 0.5); border-radius: 10px; border: 1px solid rgba(76, 76, 82, 0.4); box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); transition: transform 0.2s ease-in-out; text-align: center; max-width: 320px; margin: auto;"> | ||
<a href="black-and-white-image-colorizer" style="color: white; text-decoration: none; display: block;"> | ||
<img src="https://gts.ai/wp-content/uploads/2024/05/teaser-1-1024x613.webp" alt="" style="width: 100%; height: 150px; object-fit: cover; border-radius: 8px; transition: transform 0.2s;"> | ||
<div style="padding: 0.8rem;"> | ||
<h3 style="margin: 0; font-size: 18px;">Black and White Image Colorizer</h3> | ||
<p style="font-size: 14px; opacity: 0.8;">Colorization of Black and White Images using OpenCV and pre-trained caffe models.</p> | ||
<p style="font-size: 12px; opacity: 0.6;">📅 2025-01-14 | ⏱️ 8 min read</p> | ||
</div> | ||
</a> | ||
</figure> | ||
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</div> |
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# 📝 How to Contribute? | ||
# 📝 Contribute to AI-Code 🚀 | ||
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Welcome to the **AI-Code** project! Whether you're a seasoned developer or just starting, this guide will help you contribute systematically and effectively. Let's build amazing AI projects together! 🚀 | ||
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--- | ||
Welcome to **AI-Code**! Whether you're an expert or a beginner, your contributions matter. Let's build AI projects together! | ||
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## Getting Started | ||
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### 🌟 Star This Repository | ||
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Show your support by starring the project! 🌟 This helps others discover and contribute. Click [here](https://github.com/Avdhesh-Varshney/AI-Code) to star. | ||
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### 🍴 Fork the Repository | ||
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Create a personal copy of the repository by clicking the **Fork** button at the top right corner of the GitHub page. | ||
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### 📥 Clone Your Forked Repository | ||
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Clone your forked repository to your local machine using: | ||
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```bash | ||
git clone https://github.com/<your-github-username>/AI-Code.git | ||
``` | ||
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### 📂 Navigate to the Project Directory | ||
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Move into the directory where you've cloned the project: | ||
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```bash | ||
cd AI-Code | ||
``` | ||
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### 🌱 Create a New Branch | ||
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Create a separate branch for your changes to keep the `main` branch clean: | ||
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```bash | ||
git checkout -b <your_branch_name> | ||
``` | ||
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--- | ||
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### 🛠️ Set Up the Development Environment | ||
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#### 1. Create a Virtual Environment | ||
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To isolate dependencies, create a virtual environment: | ||
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```bash | ||
python -m venv myenv | ||
``` | ||
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#### 2. Activate the Virtual Environment | ||
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- **Windows:** | ||
```bash | ||
myenv\Scripts\activate | ||
``` | ||
- **macOS/Linux:** | ||
```bash | ||
source myenv/bin/activate | ||
``` | ||
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#### 3. Install Required Dependencies | ||
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Install all dependencies listed in the `requirements.txt` file: | ||
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```bash | ||
pip install -r requirements.txt | ||
``` | ||
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#### 4. Preview Locally | ||
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Use MkDocs to start the development server and preview the project: | ||
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```bash | ||
mkdocs serve | ||
``` | ||
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Access the site locally at: | ||
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``` | ||
http://127.0.0.1:8000/AI-Code/ | ||
``` | ||
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--- | ||
1. **Star & Fork:** [Star](https://github.com/Avdhesh-Varshney/AI-Code) ⭐ & fork the repo. | ||
2. **Clone:** | ||
```bash | ||
git clone https://github.com/<your-github-username>/AI-Code.git && cd AI-Code | ||
``` | ||
3. **Create Branch:** | ||
```bash | ||
git checkout -b <your_branch_name> | ||
``` | ||
4. **Set Up Environment:** | ||
```bash | ||
python -m venv env && source env/bin/activate # (Windows: env\Scripts\activate) | ||
pip install -r requirements.txt | ||
``` | ||
5. **Preview Locally:** | ||
```bash | ||
mkdocs serve # Visit http://127.0.0.1:8000/AI-Code/ | ||
``` | ||
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## Making Contributions | ||
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### ✏️ Make Changes | ||
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Make your desired code edits, add features, or improve documentation. Follow the project's coding standards and contribution guidelines for consistency. | ||
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### 💾 Stage and Commit Changes | ||
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#### 1. Stage All Changes: | ||
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```bash | ||
git add . | ||
``` | ||
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#### 2. Commit Changes with a Descriptive Message: | ||
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```bash | ||
git commit -m "<your_commit_message>" | ||
``` | ||
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### 🚀 Push Your Changes | ||
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Push your branch to your forked repository: | ||
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```bash | ||
git push -u origin <your_branch_name> | ||
``` | ||
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### 📝 Create a Pull Request | ||
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1. Navigate to your forked repository on GitHub. | ||
2. Click Pull Requests, then New Pull Request. | ||
3. Select your branch and describe your changes clearly before submitting. | ||
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--- | ||
1. **Edit Code:** Follow project standards. | ||
2. **Stage & Commit:** | ||
```bash | ||
git add . && git commit -m "<your_commit_message>" | ||
``` | ||
3. **Push Changes:** | ||
```bash | ||
git push -u origin <your_branch_name> | ||
``` | ||
4. **Create a Pull Request (PR):** | ||
- Go to GitHub → Open a PR → Provide clear details. | ||
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## Contribution Guidelines | ||
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### 📂 File Naming Conventions | ||
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- Use `kebab-case` for file names (e.g., `ai-code-example`). | ||
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### 📚 Documentation Standards | ||
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- Follow the [PROJECT README TEMPLATE](./project-readme-template.md) and [ALGORITHM README TEMPLATE](./algorithm-readme-template.md). | ||
- Use raw URLs for images and videos rather than direct uploads. | ||
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### 💻 Commit Best Practices | ||
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- Keep commits concise and descriptive. | ||
- Group related changes into a single commit. | ||
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### 🔀 Pull Request Guidelines | ||
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- Do not commit directly to the `main` branch. | ||
- Use the PR Template and provide all requested details. | ||
- Include screenshots, video demonstrations, or work samples for UI/UX changes. | ||
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### 🧑💻 Code Quality Standards | ||
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- Write clean, maintainable, and well-commented code. | ||
- Ensure originality and adherence to project standards. | ||
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--- | ||
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## 📘 Learning Resources | ||
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### 🧑💻 Git & GitHub Basics | ||
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- [Forking a Repository](https://help.github.com/en/github/getting-started-with-github/fork-a-repo) | ||
- [Cloning a Repository](https://help.github.com/en/desktop/contributing-to-projects/creating-an-issue-or-pull-request) | ||
- [Creating a Pull Request](https://opensource.com/article/19/7/create-pull-request-github) | ||
- [GitHub Learning Lab](https://lab.github.com/githubtraining/introduction-to-github) | ||
- **File Naming:** Use `kebab-case` (e.g., `ai-model.py`). | ||
- **Docs:** Follow [README Template](./project-readme-template.md). | ||
- **Commits:** Keep them concise & meaningful. | ||
- **PRs:** No direct commits to `main`, use PR templates, and include screenshots if relevant. | ||
- **Code Quality:** Clean, maintainable & well-commented. | ||
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### 💻 General Programming | ||
## Resources | ||
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- [Learn Python](https://www.learnpython.org/) | ||
- [MkDocs Documentation](https://www.mkdocs.org/) | ||
- **Git & GitHub:** [Fork](https://help.github.com/en/github/getting-started-with-github/fork-a-repo), [Clone](https://help.github.com/en/desktop/contributing-to-projects/creating-an-issue-or-pull-request), [PR Guide](https://opensource.com/article/19/7/create-pull-request-github) | ||
- **Learn Python:** [LearnPython.org](https://www.learnpython.org/) | ||
- **MkDocs:** [Documentation](https://www.mkdocs.org/) |
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# 📊 Data Visualization | ||
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<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(280px, 1fr)); gap: 15px; padding: 10px;"> | ||
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<!-- Bangladesh Premier League Analysis --> | ||
<figure style="padding: 1rem; background: rgba(39, 39, 43, 0.5); border-radius: 10px; box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); transition: transform 0.2s ease-in-out; text-align: center; max-width: 320px; margin: auto;"> | ||
<a href="bangladesh-premier-league-analysis" style="color: white; text-decoration: none; display: block;"> | ||
<img src="https://static.toiimg.com/thumb/msid-88446922,width-1280,height-720,resizemode-4/88446922.jpg" | ||
alt="BPL Analysis" | ||
style="width: 100%; height: 150px; object-fit: cover; border-radius: 8px; transition: transform 0.2s;"> | ||
<div style="padding: 0.8rem;"> | ||
<h3 style="margin: 0; font-size: 18px;">Bangladesh Premier League</h3> | ||
<p style="font-size: 14px; opacity: 0.8;">Team performances, player stats & key insights.</p> | ||
<p style="font-size: 12px; opacity: 0.6;">📅 2025-01-10 | ⏱️ 10 min read</p> | ||
</div> | ||
</a> | ||
</figure> | ||
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</div> |
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# Deep Learning ✨ | ||
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<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(280px, 1fr)); gap: 15px; padding: 10px;"> | ||
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<!-- Brain Tumor Detection Model --> | ||
<figure style="padding: 1rem; background: rgba(39, 39, 43, 0.5); border-radius: 10px; border: 1px solid rgba(76, 76, 82, 0.4); box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); transition: transform 0.2s ease-in-out; text-align: center; max-width: 320px; margin: auto;"> | ||
<a href="brain-tumor-detection-model" style="color: white; text-decoration: none; display: block;"> | ||
<img src="https://t3.ftcdn.net/jpg/02/61/57/66/360_F_261576629_qbzv83cBaYxMjBCTtY85cHyTK2GFRvk7.jpg" alt="" style="width: 100%; height: 150px; object-fit: cover; border-radius: 8px; transition: transform 0.2s;" /> | ||
<div style="padding: 0.8rem;"> | ||
<h3 style="margin: 0; font-size: 18px;">Brain Tumor Detection Model</h3> | ||
<p style="font-size: 14px; opacity: 0.8;">Deep learning algorithm for image and video recognition.</p> | ||
<p style="font-size: 12px; opacity: 0.6;">📅 2025-01-10 | ⏱️ 10 mins</p> | ||
</div> | ||
</a> | ||
</figure> | ||
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<!-- Music Genre Classification Model --> | ||
<figure style="padding: 1rem; background: rgba(39, 39, 43, 0.5); border-radius: 10px; border: 1px solid rgba(76, 76, 82, 0.4); box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); transition: transform 0.2s ease-in-out; text-align: center; max-width: 320px; margin: auto;"> | ||
<a href="music-genre-classification-model" style="color: white; text-decoration: none; display: block;"> | ||
<img src="https://user-images.githubusercontent.com/81585804/204538070-b036f85f-a95b-4a92-858c-d64687081f1a.png" alt="" style="width: 100%; height: 150px; object-fit: cover; border-radius: 8px; transition: transform 0.2s;"> | ||
<div style="padding: 0.8rem;"> | ||
<h3 style="margin: 0; font-size: 18px;">Music Genre Classification Model</h3> | ||
<p style="font-size: 14px; opacity: 0.8;">Unlock the rhythm of sound with AI-powered music genre classification using OpenCV!</p> | ||
<p style="font-size: 12px; opacity: 0.6;">📅 2025-01-10 | ⏱️ 12 min read</p> | ||
</div> | ||
</a> | ||
</figure> | ||
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<!-- LSTM Autoencoder for Time Series Anomaly Detection --> | ||
<figure style="padding: 1rem; background: rgba(39, 39, 43, 0.5); border-radius: 10px; border: 1px solid rgba(76, 76, 82, 0.4); box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); transition: transform 0.2s ease-in-out; text-align: center; max-width: 320px; margin: auto;"> | ||
<a href="anamoly-detection" style="color: white; text-decoration: none; display: block;"> | ||
<img src="https://fr.mathworks.com/help/examples/nnet/win64/TimeSeriesAnomalyDetectionUsingDeepLearningExample_08.png" alt="" style="width: 100%; height: 150px; object-fit: cover; border-radius: 8px; transition: transform 0.2s;"> | ||
<div style="padding: 0.8rem;"> | ||
<h3 style="margin: 0; font-size: 18px;">Time Series Anomaly Detection</h3> | ||
<p style="font-size: 14px; opacity: 0.8;">A deep learning approach to detect anomalies in time series data.</p> | ||
<p style="font-size: 12px; opacity: 0.6;">📅 2025-02-12 | ⏱️ 10 mins</p> | ||
</div> | ||
</a> | ||
</figure> | ||
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</div> |
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# Generative Adversarial Networks 💱 | ||
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<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(280px, 1fr)); gap: 15px; padding: 10px;"> | ||
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</div> |
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