Popular GitHub Repositories for Flowers

基于 AI 的代码安全审计工具，支持多种编程语言的代码分析，可以帮助开发者快速发现代码中的潜在安全漏洞。支持DeepSeek-R1，ChatGPT-4o等多种大模型。

Sample app that predicts the flower type on an image, using Core ML and the Oxford 102 category flower dataset.

A tutorial that guides users through the process of fine-tuning a stable diffusion model using HuggingFace's diffusers library. The tutorial includes advice on suitable hardware requirements, data preparation using the BLIP Flowers Dataset and a Python notebook, and detailed instructions for fine-tuning the model.

Generating cats with DCGAN and WGAN-GP.

Automated flower species classification for generating honey-bee foraging maps from drone imagery

Interface for generating ?flowers? using GANs

Convolutional neural network code for colorization and up-scaling of grayscale flowers images.

In this Project we classify different categories of Flowers using a Pre-Trained model and also using the functionality of Streamlit Application to build an API or frontend for the Project along with the various libraries of python for proper functioning of Model.

Final assignment in the NLP course at the Technion (IEM097215). In this assignment we propose a novel architecture to handle both Text-to-Image translation and Image-to-Text translation tasks on paired data, using a unified architecture of transformers and CNNs and enforcing cycle consistency.

Developed an android mobile app (GreenFinder), trained, and evaluated two deep learning image classification models for the use-case. The mobile app classifies scanned fruits, vegetables and flowers, as well as provides knowledgeable information on each classified item.

Classification of flowers , by finetuning Resnets and Inception models also image augmentation and random image erasing

Official repository of the RecSys 2025 paper "You Don't Bring Me Flowers: Mitigating Unwanted Recommendations Through Conformal Risk Control"

Classification of flowers using Convolutional Neural Network

Learn AI by create flowers detection.

A deep-learning android app to detect and classify fruits, vegetables and flowers, while providing corresponding knowledgeable information.

This project aims to create a deep learning model suitable in a mobile context that can recognize flowers from images.

I built a Python application that trained an image classifier on an Oxford flower dataset to recognize different species of flowers, and then predicted new flower images using the trained model. This project is a starting point in the world of deep learning and neural networks, implemented here using Keras, TensorFlow and transfer learning techniques.