project template added for issue abhisheks008#417

High Throughput Algae Cell Detection/.gitignore

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+/Dataset

High Throughput Algae Cell Detection/Model/README.md

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+Sure, here's an emojified version:
+
+# 🌿 High Throughput Algae Cell Detection 🔍
+
+## 🚀 Project Overview
+
+ **📌 Project Title**: High Throughput Algae Cell Detection
+
+ **🎯 Aim**: The aim of this project is to detect high throughput algae cells using Deep Learning and OpenCV methods.
+
+ **📊 Dataset**: [High Throughput Algae Cell Detection Dataset](https://www.kaggle.com/datasets/marquis03/high-throughput-algae-cell-detection)
+
+## 🛠 Approach
+
+I'm planning to explore the following models for the project:
+
+1. [Xception](https://keras.io/api/applications/xception) 🧠
+2. [ConvNeXtTiny](https://keras.io/api/applications/convnext/#convnexttiny-function) 🕹️
+3. [InceptionV3](https://keras.io/api/applications/inceptionv3) 🌀
+4. [YOLOv8m](https://github.com/ultralytics/ultralytics) 🚀
+
+**Reason for Choosing These Models:**
+All mentioned models have approximately close parameters, making them suitable for a comprehensive comparison. I have previous experience working with both pre-trained CNN architectures and YOLOv8 base architectures (tiny and base) for projects like [face-mask-detection](https://github.com/ARPIT2128/SAP-internal-face-mask-detection) and more.
+
+### 📚 Dataset and Models Used
+
+I'll be using the [dataset](https://www.kaggle.com/datasets/marquis03/high-throughput-algae-cell-detection) provided in the project. One of the approaches I recently went through was using [YOLOV5](https://www.kaggle.com/code/marquis03/yolov5-high-throughput-algae-cell-detection) for this dataset (YOLOV5 links to the notebook mentioning the approach).
+
+## 🚀 Getting Started
+
+To get started with the project, follow these steps:
+
+1. Clone the repository:
+   ```bash
+   git clone https://github.com/abhisheks008/DL-Simplified.git
+   cd High Throughput Algae Cell Detection
+   ```
+
+2. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. Download the dataset from [Kaggle](https://www.kaggle.com/datasets/marquis03/high-throughput-algae-cell-detection) and place it in the `Dataset/` directory (create if not exist).
+
+4. Run the notebooks for each model to train and evaluate the performance.
+
+## 📂 Directory Structure
+
+```plaintext
+- Dataset/
+  - high_throughput_algae_cell_detection/
+    - train/
+    - test/
+- Models/
+  - Xception_Model.ipynb
+  - ConvNeXtTiny_Model.ipynb
+  - InceptionV3_Model.ipynb
+  - YOLOv8m_Model.ipynb
+- README.md
+- requirements.txt
+```