P&ID Image Detection & Annotation Tool
Budget: $250 – $350 USD
We are seeking an experienced developer or a development team to build a robust image detection and marking tool specifically designed for processing Piping and Instrumentation Diagrams (P&ID). The tool should automatically detect equipment, nodes, and devices from uploaded P&ID images based on a provided dataset (Kaggle dataset, along with additional custom datasets we will supply).
Key Functionalities Required:
Image Recognition & Detection:
Automatically detect equipment, devices, and nodes from uploaded P&ID images.
Utilize a combination of publicly available datasets (e.g., Kaggle) and custom datasets provided by us.
Line and Node Identification:
Detect and trace connecting lines between different nodes, replicating manual identification methods accurately.
Clearly mark and annotate detected components on the images, similar to manual marking by experts.
User Interface & Experience:
Intuitive and user-friendly interface for easy uploading and visualization of marked diagrams.
Allow manual adjustments or corrections to automated markings by users.
Deployment & Platforms:
The solution must be accessible both as a Web Application and as a Mobile Application (compatible with Android and iOS).
Technical Expectations:
Utilization of modern computer vision libraries/frameworks (TensorFlow, PyTorch, OpenCV, etc.).
Scalable architecture suitable for handling multiple concurrent users.
Clear documentation of the development process and functionalities.
Ongoing support and maintenance opportunities after the initial deployment.
Deliverables:
Fully functional web and mobile applications.
Source code with comprehensive documentation.
Integration instructions for datasets and customization guides.
Preferred Qualifications:
Proven experience in computer vision, image processing, and machine learning.
Familiarity with handling engineering or industrial diagrammatic data.
Portfolio demonstrating similar image recognition and marking projects.
Key Functionalities Required:
Image Recognition & Detection:
Automatically detect equipment, devices, and nodes from uploaded P&ID images.
Utilize a combination of publicly available datasets (e.g., Kaggle) and custom datasets provided by us.
Line and Node Identification:
Detect and trace connecting lines between different nodes, replicating manual identification methods accurately.
Clearly mark and annotate detected components on the images, similar to manual marking by experts.
User Interface & Experience:
Intuitive and user-friendly interface for easy uploading and visualization of marked diagrams.
Allow manual adjustments or corrections to automated markings by users.
Deployment & Platforms:
The solution must be accessible both as a Web Application and as a Mobile Application (compatible with Android and iOS).
Technical Expectations:
Utilization of modern computer vision libraries/frameworks (TensorFlow, PyTorch, OpenCV, etc.).
Scalable architecture suitable for handling multiple concurrent users.
Clear documentation of the development process and functionalities.
Ongoing support and maintenance opportunities after the initial deployment.
Deliverables:
Fully functional web and mobile applications.
Source code with comprehensive documentation.
Integration instructions for datasets and customization guides.
Preferred Qualifications:
Proven experience in computer vision, image processing, and machine learning.
Familiarity with handling engineering or industrial diagrammatic data.
Portfolio demonstrating similar image recognition and marking projects.