Neural network that identifies and labels vegetables
-
Updated
Jun 6, 2024 - Python
Neural network that identifies and labels vegetables
This project's aim is to categorize ecommerce products from their images. MobileNetV2 model fine-tuned with 18K retail product images accross 9 categories. Project deployed with Flask and containerized via docker
Butterfly Classifier Inference API. Finetuned using MobileNetV2.
Final Year project developed using MobileNetV2 and implemented REST API using Django
This Python script calculates the similarity between a base image and a dataset of images using structural similarity and color histogram comparison. The results are sorted by similarity, can be showed with matplotlib and saved to a JSON file.
This is a pytorch repository of YOLOv4, attentive YOLOv4 and mobilenet YOLOv4 with PASCAL VOC and COCO
2024-1 XAI611 고급빅데이터분석 Project Proposal
A project requirement for the subject 'CS333-M - Data Analytics'
Your Friendly Neighborhood GPU Superhero Fighting COVID in Real-Time! With the power of MobileNetV2 and a lightning-fast NVIDIA RTX 3060, this system detects facemasks at warp speed (60 frames per second), ensuring safety with a 95% accuracy rate.
A video summarization algorithm detects essential events from the surveillance stream and can help index and efficiently retrieve required data from massive datasets.
PyTorch Implementation of MobileNetV2
Train and predict your model on pre-trained deep learning models through the GUI (web app). No more many parameters, no more data preprocessing.
Implementation of MobileNetv2
Classification models with pretrained backbones. PyTorch. Easy to use baseline to train your models
A low-cost AI-based screening system that can be installed at various locations. The objective of our solution is to automate the task of face mask detection, check for social distancing and body temperature scanning. Our proposed model outperformed other existing solutions by achieving an accuracy of 99% and an F1 score of 0.99.
EfficientNet, MobileNetV3, MobileNetV2, MixNet, etc in JAX w/ Flax Linen and Objax
Hand washing movement classification
This is a simple Python Flask application that utilizes the MobileNetV2 model for image recognition. The application allows you to upload an image, and it will predict the object present in the image.
An image classification model trained on animal-10 dataset using MobileNetV2
Add a description, image, and links to the mobilenetv2 topic page so that developers can more easily learn about it.
To associate your repository with the mobilenetv2 topic, visit your repo's landing page and select "manage topics."