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+---
+title: Baseer Self-Driving API
+emoji: 🚗
+colorFrom: blue
+colorTo: red
+sdk: docker
+app_port: 7860
+pinned: true
+license: mit
+short_description: A RESTful API for an InterFuser-based self-driving model.
+tags:
+  - computer-vision
+  - autonomous-driving
+  - deep-learning
+  - fastapi
+  - pytorch
+  - interfuser
+  - graduation-project
+  - carla
+  - self-driving
+---
+
+# 🚗 Baseer Self-Driving API
+
+| Service | Status |
+|---|---|
+| **API Status** | [![Status](https://img.shields.io/website?up_message=online&down_message=offline&url=https%3A%2F%2FBaseerAI-baseer-server.hf.space)](https://BaseerAI-baseer-server.hf.space) |
+| **Model** | [![Model](https://img.shields.io/badge/Model-Interfuser--Baseer--v1-blue)](https://huggingface.co/BaseerAI/Interfuser-Baseer-v1) |
+| **Frameworks** | [![FastAPI](https://img.shields.io/badge/FastAPI-005571?style=flat&logo=fastapi)](https://fastapi.tiangolo.com/) [![PyTorch](https://img.shields.io/badge/PyTorch-%23EE4C2C.svg?style=flat&logo=PyTorch&logoColor=white)](https://pytorch.org/) |
+
+## 📋 Project Description
+
+**Baseer** is an advanced self-driving system that provides a robust, real-time API for autonomous vehicle control. This Space hosts the FastAPI server that acts as an interface to the fine-tuned **[Interfuser-Baseer-v1](https://huggingface.co/BaseerAI/Interfuser-Baseer-v1)** model.
+
+The system is designed to take a live camera feed and vehicle measurements, process them through the deep learning model, and return actionable control commands and a comprehensive scene analysis.
+
+---
+
+## 🏗️ Architecture
+
+This project follows a decoupled client-server architecture, where the model and the application are managed separately for better modularity and scalability.
+
+```
++-----------+    +------------------------+    +--------------------------+
+|           |    |                        |    |                          |
+|  Client   | -> |   Baseer API (Space)   | -> |  Interfuser Model (Hub)  |
+|(e.g.CARLA)|    |   (FastAPI Server)     |    | (Private/Gated Weights)  |
+|           |    |                        |    |                          |
++-----------+    +------------------------+    +--------------------------+
+     HTTP              Loads Model                    Model Repository
+   Request
+```
+
+## ✨ Key Features
+
+### 🧠 **Advanced Perception Engine**
+- **Powered by:** The [Interfuser-Baseer-v1](https://huggingface.co/BaseerAI/Interfuser-Baseer-v1) model.
+- **Focus:** High-accuracy traffic object detection and safe waypoint prediction.
+- **Scene Analysis:** Real-time assessment of junctions, traffic lights, and stop signs.
+
+### ⚡ **High-Performance API**
+- **Framework:** Built with **FastAPI** for high throughput and low latency.
+- **Stateful Sessions:** Manages multiple, independent driving sessions, each with its own tracker and controller state.
+- **RESTful Interface:** Intuitive and easy-to-use API design.
+
+### 📊 **Comprehensive Outputs**
+- **Control Commands:** `steer`, `throttle`, `brake`.
+- **Scene Analysis:** Probabilities for junctions, traffic lights, and stop signs.
+- **Predicted Waypoints:** The model's intended path for the next 10 steps.
+- **Visual Dashboard:** A generated image that provides a complete, human-readable overview of the current state.
+
+---
+
+## 🚀 How to Use
+
+Interact with the API by making HTTP requests to its endpoints. The typical workflow is to start a session, run steps in a loop, and then end the session.
+
+### 1. Start a New Session
+This will initialize a new set of tracker and controller instances on the server.
+
+**Request:**
+```bash
+curl -X POST "https://BaseerAI-baseer-server.hf.space/start_session"
+```
+
+**Example Response:**
+```json
+{
+  "session_id": "a1b2c3d4-e5f6-7890-1234-567890abcdef"
+}
+```
+
+### 2. Run a Simulation Step
+
+Send the current camera view and vehicle measurements to be processed. The API will return control commands and a full analysis.
+
+**Request:**
+```bash
+curl -X POST "https://BaseerAI-baseer-server.hf.space/run_step" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "session_id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
+    "image_b64": "your-base64-encoded-bgr-image-string",
+    "measurements": {
+      "pos_global": [105.0, -20.0],
+      "theta": 1.57,
+      "speed": 5.5,
+      "target_point": [10.0, 0.0]
+    }
+  }'
+```
+
+**Example Response:**
+```json
+{
+  "control_commands": {
+    "steer": 0.05,
+    "throttle": 0.6,
+    "brake": false
+  },
+  "scene_analysis": {
+    "is_junction": 0.02,
+    "traffic_light_state": 0.95,
+    "stop_sign": 0.01
+  },
+  "predicted_waypoints": [
+    [1.0, 0.05],
+    [2.0, 0.06],
+    [3.0, 0.07],
+    [4.0, 0.07],
+    [5.0, 0.08],
+    [6.0, 0.08],
+    [7.0, 0.09],
+    [8.0, 0.09],
+    [9.0, 0.10],
+    [10.0, 0.10]
+  ],
+  "dashboard_b64": "a-very-long-base64-string-representing-the-dashboard-image...",
+  "reason": "Red Light"
+}
+```
+
+**Response Fields:**
+- **`control_commands`**: The final commands to be applied to the vehicle.
+- **`scene_analysis`**: Probabilities for different road hazards. A high `traffic_light_state` value (e.g., > 0.5) indicates a red light.
+- **`predicted_waypoints`**: The model's intended path, relative to the vehicle.
+- **`dashboard_b64`**: A Base64-encoded JPEG image of the full dashboard view, which can be directly displayed in a client application.
+- **`reason`**: A human-readable string explaining the primary reason for the control action (e.g., "Following ID 12", "Red Light", "Cruising").
+
+### 3. End the Session
+
+This will clean up the session data from the server.
+
+**Request:**
+```bash
+curl -X POST "https://BaseerAI-baseer-server.hf.space/end_session?session_id=a1b2c3d4-e5f6-7890-1234-567890abcdef"
+```
+
+**Example Response:**
+```json
+{
+  "message": "Session a1b2c3d4-e5f6-7890-1234-567890abcdef ended."
+}
+```
+
+---
+
+## 📡 API Endpoints
+
+| Endpoint | Method | Description |
+|---|---|---|
+| `/` | GET | Landing page with API status. |
+| `/docs` | GET | Interactive API documentation (Swagger UI). |
+| `/start_session` | POST | Initializes a new driving session. |
+| `/run_step` | POST | Processes a single frame and returns control commands. |
+| `/end_session` | POST | Terminates a specific session. |
+| `/sessions` | GET | Lists all currently active sessions. |
+
+---
+
+## 🎯 Intended Use Cases & Limitations
+
+### ✅ Optimal Use Cases
+- Simulating driving in CARLA environments.
+- Research in end-to-end autonomous driving.
+- Testing perception and control modules in a closed-loop system.
+- Real-time object detection and trajectory planning.
+
+### ⚠️ Limitations
+- **Simulation-Only:** Trained exclusively on CARLA data. Not suitable for real-world driving.
+- **Vision-Based:** Relies on a single front-facing camera and has inherent blind spots.
+- **No LiDAR:** Lacks the robustness of sensor fusion in adverse conditions.
+
+---
+
+## 🛠️ Development
+
+This project is part of a graduation thesis in Artificial Intelligence.
+- **Deep Learning:** PyTorch
+- **API Server:** FastAPI
+- **Image Processing:** OpenCV
+- **Scientific Computing:** NumPy
+
+## 📞 Contact
+
+For inquiries or support, please use the **Community** tab in this Space or open an issue in the project's GitHub repository (if available).
+
+---
+
+**Developed by:** Adam Altawil  
+**License:** MIT