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## RGB.ipynb

      
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                soumya997
                / RGB.ipynb
            
            
              Created
              March 29, 2020 17:07
            
          
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## python_rgb.py
###IMPORTING LIBRARIES###
import cv2
import numpy as np
import matplotlib.pyplot as plt
import os
from tqdm import tqdm
%matplotlib inline

## python_rgb_1.py
Z,X=[],[]
IMG_SIZE=150
FLOWER_SUNFLOWER_DIR='../input/flowers-recognition/flowers/flowers/sunflower'
def assign_label(img,flower_type):
    return flower_type
def make_train_data(flower_type,DIR):
    for img in tqdm(os.listdir(DIR)):
        label=assign_label(img,flower_type)
        path = os.path.join(DIR,img)
        img = cv2.imread(path,cv2.IMREAD_COLOR)

## python_rgb_2.py
make_train_data('Sunflower',FLOWER_SUNFLOWER_DIR)  #####Loading Sunflower Data
fix_img = cv2.cvtColor(X[0],cv2.COLOR_BGR2RGB)    ###########CONVERTING BGR COLOR SPACE INTO RGB COLOR SPACE #########
new_img_1 = fix_img.copy()
new_img_2 = fix_img.copy()
new_img_3 = fix_img.copy()
new_img_1[:,:,0] = 0 # making R channel zero    ####For BLUE channel#####
new_img_1[:,:,1] = 0 #making G channel zero
new_img_2[:,:,1] = 0####For RED color Channel####
new_img_2[:,:,2] = 0
new_img_3[:,:,0] = 0###For GREEN Channel####

## python_rgb_3.py
f, axes = plt.subplots(1,3, figsize = (15,15))
list = [new_img_1,new_img_2,new_img_3]
i = 0
for ax in axes:
    ax.imshow(list[i])
    i+=1

## python_rgb_4.py
hsl_img = cv2.cvtColor(X[0],cv2.COLOR_BGR2HLS)  #### CONVERTING BGR COLOR SPACE INTO HSL COLOR SPACE  ####
hsl_img_1 = hsl_img.copy()
hsl_img_2 = hsl_img.copy()
hsl_img_3 = hsl_img.copy()
hsl_img_1[:,:,1] = 0  #### HUE --> ZERO  ####
hsl_img_1[:,:,2] = 0
hsl_img_2[:,:,0] = 0  #### SATURATION --> ZERO ####
hsl_img_2[:,:,2] = 0
hsl_img_3[:,:,0] = 0  #### LIGHTNESS --> ZERO ####
hsl_img_3[:,:,1] = 0

## python_rgb_4.py
f, axes = plt.subplots(1,3, figsize = (15,15))
list = [hsl_img_1,hsl_img_2,hsl_img_3]
i = 0
for ax in axes:
    ax.imshow(list[i])
    i+=1

## python_rgb_5.py
hsv_img = cv2.cvtColor(X[0],cv2.COLOR_BGR2HSV)
hsv_img_1 = hsv_img.copy()
hsv_img_2 = hsv_img.copy()
hsv_img_3 = hsv_img.copy()
hsv_img_1[:,:,1] = 0#HUE --> ZERO
hsv_img_1[:,:,2] = 0
hsv_img_2[:,:,0] = 0#SATURATION --> ZERO
hsv_img_2[:,:,2] = 0
hsv_img_3[:,:,0] = 0#VALUE --> ZERO
hsv_img_3[:,:,1] = 0

## python_rgb_6.py
f, axes = plt.subplots(1,3, figsize = (15,15))
list = [hsv_img_1,hsv_img_2,hsv_img_3]
i = 0
for ax in axes:
    ax.imshow(list[i])
    i+=1

## gsoc-scraper.py
import pickle
import time

import pandas as pd

from selenium import webdriver
import selenium.webdriver.support.ui as ui

def get_list(tags) -> str:
    '''Converts list of tags to data string.'''
	###IMPORTING LIBRARIES###
	import cv2
	import numpy as np
	import matplotlib.pyplot as plt
	import os
	from tqdm import tqdm
	%matplotlib inline
	Z,X=[],[]
	IMG_SIZE=150
	FLOWER_SUNFLOWER_DIR='../input/flowers-recognition/flowers/flowers/sunflower'
	def assign_label(img,flower_type):
	return flower_type
	def make_train_data(flower_type,DIR):
	for img in tqdm(os.listdir(DIR)):
	label=assign_label(img,flower_type)
	path = os.path.join(DIR,img)
	img = cv2.imread(path,cv2.IMREAD_COLOR)
	make_train_data('Sunflower',FLOWER_SUNFLOWER_DIR) #####Loading Sunflower Data
	fix_img = cv2.cvtColor(X[0],cv2.COLOR_BGR2RGB) ###########CONVERTING BGR COLOR SPACE INTO RGB COLOR SPACE #########
	new_img_1 = fix_img.copy()
	new_img_2 = fix_img.copy()
	new_img_3 = fix_img.copy()
	new_img_1[:,:,0] = 0 # making R channel zero ####For BLUE channel#####
	new_img_1[:,:,1] = 0 #making G channel zero
	new_img_2[:,:,1] = 0####For RED color Channel####
	new_img_2[:,:,2] = 0
	new_img_3[:,:,0] = 0###For GREEN Channel####
	f, axes = plt.subplots(1,3, figsize = (15,15))
	list = [new_img_1,new_img_2,new_img_3]
	i = 0
	for ax in axes:
	ax.imshow(list[i])
	i+=1
	hsl_img = cv2.cvtColor(X[0],cv2.COLOR_BGR2HLS) #### CONVERTING BGR COLOR SPACE INTO HSL COLOR SPACE ####
	hsl_img_1 = hsl_img.copy()
	hsl_img_2 = hsl_img.copy()
	hsl_img_3 = hsl_img.copy()
	hsl_img_1[:,:,1] = 0 #### HUE --> ZERO ####
	hsl_img_1[:,:,2] = 0
	hsl_img_2[:,:,0] = 0 #### SATURATION --> ZERO ####
	hsl_img_2[:,:,2] = 0
	hsl_img_3[:,:,0] = 0 #### LIGHTNESS --> ZERO ####
	hsl_img_3[:,:,1] = 0
	f, axes = plt.subplots(1,3, figsize = (15,15))
	list = [hsl_img_1,hsl_img_2,hsl_img_3]
	i = 0
	for ax in axes:
	ax.imshow(list[i])
	i+=1
	hsv_img = cv2.cvtColor(X[0],cv2.COLOR_BGR2HSV)
	hsv_img_1 = hsv_img.copy()
	hsv_img_2 = hsv_img.copy()
	hsv_img_3 = hsv_img.copy()
	hsv_img_1[:,:,1] = 0#HUE --> ZERO
	hsv_img_1[:,:,2] = 0
	hsv_img_2[:,:,0] = 0#SATURATION --> ZERO
	hsv_img_2[:,:,2] = 0
	hsv_img_3[:,:,0] = 0#VALUE --> ZERO
	hsv_img_3[:,:,1] = 0
	f, axes = plt.subplots(1,3, figsize = (15,15))
	list = [hsv_img_1,hsv_img_2,hsv_img_3]
	i = 0
	for ax in axes:
	ax.imshow(list[i])
	i+=1
	import pickle
	import time

	import pandas as pd

	from selenium import webdriver
	import selenium.webdriver.support.ui as ui

	def get_list(tags) -> str:
	'''Converts list of tags to data string.'''