# Colour identification in images

## **Introduction**

Images are composed using a grid of small squares called pixels. Each pixel is assigned to a specific colour value and, when combined, creates the overall image.

To identify all the colours in the image, Python is used which has a library called OpenCV.

## **Library**

We import basic libraries including `matplotlib.pyplot` , `cv2`, `numpy`, `pandas`

```python
import cv2
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
```

pandas and numpy are used to extract the count, cv2 is used for OpenCV. matplotlib is used to plot the output.

To read any image we use cv2.imread()

```python
image = cv2.imread('link_to_image')
# if we have to resize the image then
image = cv2.resize(img, (960,540))
```

To view the read image we use matplotlib to plot the image with the following code:

```python
plt.figure(figsize=(18,6)) # used to specify the size of image
plt.imshow(img) # This shows the image
```

The image that has been read using cv2 is in the colour format of BGR so to make it in RGB format we apply the following line of code:

```python
grid_RGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
```

after formatting to RGB colour pattern we again plot the image using the above code of plt.figure().....

Reading data from filename.csv file we use pandas read\_csv

```python
csv_path = "path of csv flie e.g. './filename.csv'"
df = pd.read_csv(csv_path, names=index, header=None)
```

## **Colour Identification**

Defined a function, to achieve the colour in the given function

```python
def get_color_name(R,G,B):
    minimum = 1000
    for i in range(len(df)):
        d = abs(R - int(df.loc[i,'R'])) + abs(G - int(df.loc[i,'G'])) + abs(B-int(df.loc[i,'B']))
        if d <= minimum:
            minimum = d
            cname = df.loc[i,'color_name']
    return cname
```

Handling the mouse event.

```python
def draw_function(event, x, y, flags, params):
    if event == cv2.EVENT_LBUTTONDBLCLK:
        global b, g, r, xpos, ypos, clicked
        clicked = True
        xpos = x
        ypos = y
        b,g,r = img[y,x]
        b = int(b)
        g = int(g)
        r = int(r)
```

OpenCV window

```python
cv2.namedWindow('Color Identification in Images')
cv2.setMouseCallback('Color Identification in Images', draw_function)

while True:
    cv2.imshow('Color Identification in Images', img)
    if clicked:
        cv2.rectangle(img, (20,20), (600,60), (b,g,r), -1)

        text = get_color_name(r,g,b) + 'R = ' + str(r) + 'G = ' + str(g) + 'B = ' + str(b)
        # Draw text on image
        cv2.putText(img, text, (50,50), 2,0.8, (255,255,255) , 2 , cv2.LINE_AA)
    # exit on esc    
    if cv2.waitKey(20) & 0xFF == 27:
        break
cv2.destroyAllWindows()
```