FISH BREED CLASSIFICATION¶
IMPORT LIBRARY AND DATA¶
In [3]:
!pip install wget
import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
import seaborn as sns
import cv2
from sklearn.model_selection import StratifiedShuffleSplit,train_test_split
import glob
import tensorflow as tf
from sklearn import metrics
from tensorflow import keras
!wget -N 'https://cainvas-static.s3.amazonaws.com/media/user_data/devanshchowd/fish.tar.gz'
import tarfile
file = tarfile.open('fish.tar.gz')
file.extractall('./')
file.close()
BASIC ANALYSIS¶
In [23]:
data = pd.read_csv('fish/data.csv')
display(data)
sns.set_style('darkgrid')
sns.countplot(data = data,y = 'label')
Out[23]:
In [109]:
def get_img(index):
img = plt.imread(data.iloc[index]['path'])
return img
demo = pd.DataFrame(data.groupby('label').first()).reset_index()
fig,ax = plt.subplots(3,3,figsize=(15,15))
for i in range(3):
for j in range(3):
ax[i][j].imshow(plt.imread(demo.iloc[i*3+j].path))
ax[i][j].tick_params(left = False, bottom = False)
ax[i][j].set_xticks([])
ax[i][j].set_yticks([])
ax[i][j].set_title(demo.iloc[i*3+j].label)
display(demo)
fig.savefig('Sample.png')