flower-classification
There are 92 repositories under flower-classification topic.
Flower17
Flower Classification
Flower_Classification
PyTorch | Flask | Google Colab | Kaggle
arnica
flowersegmentationtool
PyTorch-Image-Classifier
As part of the Facebook AI scholarship challenge, I built an image classifier that identifies different species of flowers.
Image-Classifier
This is the final Project of the Udacity AI with Python Nanodegree.
FruitFlowerClassifier
Android app for Flower and Fruit Classification
Flower-Species-Prediction
Predict Flower Species with Pre-trained Model
Flower-classification
Flower Classification With Transfer Learning.
Flower-Recognition-Using-CNN
A simple web site to classify flowers into 5 classes using CNN
Flower-Classification
Multi Class Flower Image classification
Flower-Species-Prediction
A project made for internship at Coding Samurai
Logistic_Regression_Classifier
Built a classifier using Logistic Regression model to classify different species of flowers
bloomsage-ml
BloomSage ML Component
Flower-Classification-using-CNN
Classification of flowers using Convolutional Neural Network
Flower_iris
Flower_iris
k-nn-flower-classifier
This project uses the K-NN algorith to classify flowers. Written in CPP.
Flower_Classification_using_Deep_Learning
Flower Classification using Deep Learning is a computer vision project that leverages deep learning techniques to automatically classify different species of flowers based on images.
Flower-Species-Prediction-Model
Model to predict the species of Iris flower by giving various data about the flower.
AI-Flower-Classifier
The Flower Classifier is a AI Web App designed to classify pictures of flowers into five main classes: daisy, dandelion, roses, sunflowers, and tulips. It is the first application in which I practiced concepts such as Flask API and Tramsfer learning and taking AI models, deploying them on a simple web app which i dont intent to improve design lol
Image-Classifier
This repository contains a deep learning model for image classification implemented in PyTorch. It is part of the Udacity Data Science Nanodegree program, and focuses on deep learning with PyTorch for image classification of flowers.
Flower_Detector
This application detects flowers with the help of model created on google colab with python and tensorflow. for creating this application flutter and dart is used.
Project-FlowerSpecies-MachineLearning
Git repo of a flower species detection project using Random Forest ML. Classifies species based on petal/sepal length & width. Includes Python code for training, prediction & evaluation. Accurate & efficient tool for automatic flower species identification.
tulip
🌷 tulip - CNN classifying flowers from the Flower102 dataset
Flower-Breed-Image-Classifier
Project code for Udacity's AI Programming with Python Nanodegree program. In this project, code was developed for an image classifier built with PyTorch, then converted into command line applications: train.py, predict.py.The image classifier recognizes different species of flowers.
flower-species-classification
Species classification challenge as part of a course on Artificial Neural Networks and Deep Learning
mobilenet-transfer-learning-flowers
Transferring MobileNetV2's feature extractor layers to classify flower images.
ResNet-and-VGG19-Flower-dataset
Cassifying flowers by type
Flower-Classification
Used a kaggle dataset which contains the pictures that are divided into five classes: chamomile, tulip, rose, sunflower, dandelion. Trained a CNN model to extract the features and classify the images
fellowship_of_the_ring
Use a pretrained ResNet 18 and train on the Flowers dataset. Use cut-out and discriminative learning rates. Measure its effect on your model's performance.
vgg16_vgg16_scratch
build vgg16 and vgg19 network from scratch. Used flower data set which can be downloaded from kaggle
Flower-Separate
Determination of the type of flower (from a limited number of possible ones) from a photograph. The app is wrapped in an android app shell.
Image-Classifier-with-TensorFlow
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.
Transfer_Learning
Transfer Learning using Mobilenet model on a Flower Dataset
keras_flower
A simple flower classification :white_flower: python library
Petals-to-the-Metal-Flower-Classification-Kaggle
This notebook is the solution for Kaggle's Petals to the Metal - Flower Classification on TPU challenge: https://www.kaggle.com/c/tpu-getting-started