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Updated 3 years ago
!pip install jovian --upgrade --quietFlower Recognition - An Image Classification Project
About
This dataset contains 4323 images of flowers.
The data collection is based on the data flicr, google images, yandex images.
You can use this datastet to recognize plants from the photo.
Content
The pictures are divided into five classes: chamomile, tulip, rose, sunflower, dandelion.
For each class there are about 800 photos. Photos are not high resolution, about 320x240 pixels. Photos are not reduced to a single size, they have different proportions!
Acknowledgements
- How to use Kaggle Datasets in Google Colab - https://medium.com/analytics-vidhya/how-to-fetch-kaggle-datasets-into-google-colab-ea682569851a
- Reference ipynb notebook - https://colab.research.google.com/drive/1c-U-fCmpcI0TAIds4_9IatzxMkcYnY8d#scrollTo=xfPP3dVf3KUg
Importing important libraries and project creation.
import os
import torch
import torchvision
import tarfile
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from torchvision.datasets.utils import download_url
from torchvision.datasets import ImageFolder
from torch.utils.data import DataLoader
import torchvision.transforms as tt
from torch.utils.data import random_split
from torchvision.utils import make_grid
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
matplotlib.rcParams['figure.facecolor'] = '#ffffff'