object detection model fast r-cnn, trained on COCO dataset to identity 80 different objects

Author: GeoSegun

examples/deep_learning-computerVision/nvidia-fastrcnn_object_detection/README.md

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+# 🪐 Saturn Cloud Template: Object Detection with Faster R-CNN
+
+This template provides a ready-to-run **object detection project** built for **Saturn Cloud**.  
+It uses a pre-trained **Faster R-CNN** model to detect common objects in images and visualize results — all powered by **GPU acceleration**.
+
+Use this template as a **fast start** for your own computer vision or image analysis projects on Saturn Cloud.
+
+---
+
+## 🧠 What This Template Does
+
+- Load and analyze images from **local paths** or **URLs**  
+- Detect objects using a pre-trained **Faster R-CNN** model  
+- Display bounding boxes and confidence scores  
+- Run interactively from a terminal or Jupyter Notebook  
+- Easily extend to **custom training, datasets, or scaling** with Saturn Cloud’s GPU clusters  
+
+---
+
+## ⚙️ Saturn Cloud Environment Setup
+
+This template is pre-configured for **Saturn Cloud GPU environments**.  
+You can run it immediately on a GPU-backed resource — no setup required beyond installing dependencies.
+
+### Default Environment
+- **Image**: `saturncloud/pytorch:latest`  
+- **Hardware**: GPU instance (recommended: 1× NVIDIA T4 or A10G)  
+- **Python**: 3.10+  
+- **Memory**: 8GB+  
+
+### Dependencies (from `requirements.txt`)
+```
+
+torch
+torchvision
+matplotlib
+pillow
+requests
+
+````
+
+To reproduce the environment manually:
+
+```bash
+pip install -r requirements.txt
+````
+
+---
+
+## 🚀 Quickstart (in Saturn Cloud)
+
+1. **Launch this template** in your Saturn Cloud workspace:
+
+   * Go to [Saturn Cloud](https://saturncloud.io/)
+   * Click **New Project → From Template**
+   * Choose **Object Detection with Faster R-CNN**
+
+2. **Open the Jupyter notebook and run all the code cells**.
+
+3. When prompted, enter an image path or URL.
+   You can test with this example URL:
+
+   ```
+   https://plus.unsplash.com/premium_photo-1667030489905-d8e6309ebe0e?ixlib=rb-4.1.0&auto=format&fit=crop&q=60&w=200
+   ```
+
+   Output:
+
+   ```
+   📡 Downloading image from URL...
+   ✅ Image downloaded successfully
+   🎯 Detected 3 objects (threshold: 0.5):
+     1. Person: 99.3%
+     2. Dog: 97.1%
+     3. Chair: 88.4%
+   ```
+
+4. A visualization window will display the bounding boxes drawn over the detected objects.
+
+---
+
+## 🧩 Core Components
+
+### `detect_in_uploaded_image(image_input, threshold=0.5)`
+
+Detects objects in an image (from a local file or URL) using the pre-trained model.
+Returns the bounding boxes, labels, and confidence scores.
+
+---
+
+## 📚 References
+
+* [Saturn Cloud Examples Repository](https://github.com/saturncloud/examples)
+* [Faster R-CNN Model Implementation](https://github.com/trzy/FasterRCNN)
+* [COCO Dataset Classes](https://cocodataset.org/#home)
+* [Saturn Cloud Documentation](https://saturncloud.io/docs/)
+
+