Need to create People Detection Model
Budget: ₹37,500 – ₹75,000 INR
We need a computer vision model for detecting people in images or videos, and it should be optimized to work on the OpenVINO platform. We already have a dataset available for training the model.
Objectives:
The main objective of this project is to develop a people detection model that can accurately detect human beings in different environments. The model should be optimized to work on the OpenVINO platform for efficient inference.
Requirements:
Dataset: We have a dataset available for use in training the model. The dataset should be analyzed and preprocessed to ensure that it is appropriate for the model training process.
Model Architecture: The model architecture should be simple, easy to understand, and accurate in detecting people in images or videos. It should be optimized for speed and accuracy and should be able to handle different lighting conditions, backgrounds, and occlusions.
OpenVINO compatibility: The model should be optimized to work with the OpenVINO platform for efficient inference. The model should be tested on OpenVINO to ensure compatibility and optimal performance.
Performance Metrics: The model should be evaluated using standard metrics, such as precision, recall, F1 score, and accuracy, to measure its performance.
Documentation: The model should be well-documented, including all details regarding the dataset, model architecture, training process, and evaluation metrics. This documentation should be clear and easy to understand.
Code: The code for the model should be simple, easy to follow, and well-organized. It should be modular, so that individual components can be easily modified or replaced.
Conclusion:
We believe that a simple people detection model will have many practical applications in different fields. We look forward to seeing the final product and are excited to see how it can be used to improve various processes and applications.
should have experience in computer vision, specifically in developing models for object detection, and should provide examples of their previous works.
Please start the proposal with the word GreenApple
Objectives:
The main objective of this project is to develop a people detection model that can accurately detect human beings in different environments. The model should be optimized to work on the OpenVINO platform for efficient inference.
Requirements:
Dataset: We have a dataset available for use in training the model. The dataset should be analyzed and preprocessed to ensure that it is appropriate for the model training process.
Model Architecture: The model architecture should be simple, easy to understand, and accurate in detecting people in images or videos. It should be optimized for speed and accuracy and should be able to handle different lighting conditions, backgrounds, and occlusions.
OpenVINO compatibility: The model should be optimized to work with the OpenVINO platform for efficient inference. The model should be tested on OpenVINO to ensure compatibility and optimal performance.
Performance Metrics: The model should be evaluated using standard metrics, such as precision, recall, F1 score, and accuracy, to measure its performance.
Documentation: The model should be well-documented, including all details regarding the dataset, model architecture, training process, and evaluation metrics. This documentation should be clear and easy to understand.
Code: The code for the model should be simple, easy to follow, and well-organized. It should be modular, so that individual components can be easily modified or replaced.
Conclusion:
We believe that a simple people detection model will have many practical applications in different fields. We look forward to seeing the final product and are excited to see how it can be used to improve various processes and applications.
should have experience in computer vision, specifically in developing models for object detection, and should provide examples of their previous works.
Please start the proposal with the word GreenApple