Recherche de valeurs BGR moyennes pour chaque colonne dans chaque couleur

Question

Nous travaillons sur un code qui se penche sur une plaque de 96 puits. Nous avons les coordonnées des centres de chaque puits. Nous avons ensuite créé une boucle for qui nous permettrait d'obtenir la valeur BGR de chaque puits. Cependant, nous devons organiser chaque colonne et faire la moyenne de ces valeurs. Je crois que nous obtenons une erreur de la première boucle. Avec celui-ci, il semble que la fonction ne passe que par la première boucle et non par la seconde. Quand je l'exécute, j'obtiens 3 valeurs (en supposant être des valeurs bgr) et ensuite je pousse les moyennes. Il semble également répéter certaines valeurs moyennes. Toutes les suggestions à ce que je peux changer, ou les erreurs au premier coup d'oeil. Je fournirai l'image et la légende ci-dessous.

Liens vers les images sont: http://imgur.com/Eb87ZxW (l'image a été mis à l'échelle, de sorte que les coordonnées ne fonctionnent pas avec l'image téléchargée) http://imgur.com/P4tPPXX

import cv2, numpy as np, sys 

#filename will be taken from the command line and process as the image variable 
#filename= sys.argv([1]) 
img = cv2.imread('greenandblueplate.jpg') 

#centroids 
wells = [img[110,97], img[184,97], img[254,97], img[324,97], img[396,96], img[466,97], #columnH 12-7 
     img[537,96], img[607,97], img[680,96], img[750,97], img[820,96], img[891,97], #columnH 6-1 
     img[110,165],img[184,165],img[254,165],img[324,165],img[396,165],img[466,165], #columnG 12-7 
     img[537,165],img[607,165],img[680,165],img[750,166],img[820,165],img[891,165], #columnG 6-1 
     img[110,235],img[184,235],img[254,235],img[324,235],img[396,235],img[466,235], #columnF 12-7 
     img[537,235],img[607,235],img[680,235],img[750,235],img[820,235],img[891,235], #columnF 6-1 
     img[110,305],img[184,305],img[254,305],img[324,305],img[396,305],img[466,305], #columnE 12-7 
     img[537,305],img[607,305],img[680,305],img[750,305],img[820,305],img[891,305], #columnE 6-1 
     img[110,373],img[184,373],img[254,373],img[324,373],img[396,373],img[466,373], #columnD 12-7 
     img[537,373],img[607,373],img[680,373],img[750,372],img[820,373],img[891,373], #columnD 6-1 
     img[110,442],img[184,442],img[254,442],img[324,442],img[396,442],img[466,442], #columnC 12-7 
     img[537,442],img[607,442],img[680,442],img[750,443],img[820,442],img[891,442], #columnC 6-1 
     img[109,511],img[184,511],img[254,511],img[324,511],img[396,511],img[466,511], #columnB 12-7 
     img[537,512],img[607,512],img[680,511],img[750,511],img[820,511],img[891,511], #columnB 6-1 
     img[109,582],img[184,582],img[254,582],img[324,581],img[396,582],img[466,582], #columnA 12-7 
     img[537,581],img[607,582],img[680,582],img[750,581],img[820,582],img[891,582]] #columnA 6-1 

bAvgFilledWells = [] 
gAvgFilledWells = [] 
rAvgFilledWells = [] 

#filtering out the centroids that are not needed 
#and getting the bgr values for the first color on the plate 
for center in wells: 
    if center[1] > 124: 
     if center[0] < 360: 
      b = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 0] 
      g = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 1] 
      r = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 2] 
      bAvg = np.mean(b) 
      gAvg = np.mean(g) 
      rAvg = np.mean(r) 

      bAvgFilledWells.append(bAvg) 
      gAvgFilledWells.append(gAvg) 
      rAvgFilledWells.append(rAvg) 
      print(center) 
      print("For the first color, average value for blue is:", bAvg) 
      print("For the first color, average value for green is:", gAvg) 
      print("For the first color, average value for red is:", rAvg) 


bAvgFilledWells2 = [] 
gAvgFilledWells2 = [] 
rAvgFilledWells2 = [] 

#filtering out the centroids that are not needed 
#and getting the bgr values for the second color on the plate   
for center in wells: 
    if center[1] > 124: 
     if center[0] > 360 and center[0] < 642: 
      b2 = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 0] 
      g2 = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 1] 
      r2 = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 2] 
      bAvg2 = np.mean(b2) 
      gAvg2 = np.mean(g2) 
      rAvg2 = np.mean(r2) 

      print(center) 
      print("For the second color, average value for blue is:", bAvg2) 
      print("For the second color, average value for green is:", gAvg2) 
      print("For the second color, average value for blue is:", rAvg2) 
      bAvgFilledWells2.append(bAvg2) 
      gAvgFilledWells2.append(gAvg2) 
      rAvgFilledWells2.append(rAvg2) 

Answer 1

La vaste gamme wells au début semble fastidieux et répétitif. Il pourrait être amélioré en créant des listes des positions X/Y des colonnes A-H et des lignes 1-12.

Et c'est la source de vos erreurs: dans les boucles, vous analysez center comme si c'était la position x, y, mais en fait c'est le pixel récupéré de .

Au lieu de cela quelque chose comme:

columns = [110,124,160] # give 8 values for columns A-H 
rows = [97, 165, 235] # give 12 values for rows 1-12 
#... 
for row = 0 to 3: 
    for column = 0 to 7: 
     center_column = columns[column] 
     center_row = rows[row] 
     #... get img pixels and process b,g,r values 

Answer 2

Voilà comment je réécrire votre code:

import cv2 
from itertools import product 
import numpy as np 
import sys 

# image coordinates 
ROWS = (891, 820, 750, 680, 607, 537, 466, 396, 324, 254, 184, 110) # rows 1..12 
COLS = (582, 511, 442, 373, 305, 235, 165, 97)      # cols A..H 

def get_rect_avg_color(img, x, y, w=8, h=8): 
    """ 
    Return the BGR average color of a rectangular area of the image 
     centered on (x,y) with width w and height h 
    """ 
    half_w = w // 2 
    half_h = h // 2 
    # extract the rectangular area 
    rect = img[x - half_w: x + (w - half_w) + 1, y - half_h: y + (h - half_h) + 1] 
    # average each channel independantly 
    avg_col = rect.mean(axis=(0,1)) 
    return avg_col # returns [avg_b, avg_g, avg_r] 

def get_cells_avg_color(img, cells): 
    """ 
    Return the BGR average color of a list of cells 
    """ 
    cell_colors = np.vstack(get_rect_avg_color(img, *cell) for cell in cells) 
    return cell_colors.mean(axis=0) # returns [avg_b, avg_g, avg_r] 

def get_cells(col_from, col_to, row_from, row_to): 
    """ 
    Return a list of all cells in a rectangular block 

    col_from, col_to in "A".."H" 
    row_from, row_to in 1..12 

    col_to and row_to are inclusive 
    """ 
    col_from = ord(col_from.upper()) - ord("A") 
    col_to = ord(col_to .upper()) - ord("A") 
    col_from, col_to = min(col_from, col_to), max(col_from, col_to) 
    row_from -= 1 
    row_to -= 1 
    row_from, row_to = min(row_from, row_to), max(row_from, row_to) 
    return product(ROWS[row_from:row_to + 1], COLS[col_from:col_to + 1]) 

def main(img_fname): 
    img = cv2.imread(img_fname) 

    first_cells = get_cells("A", "G", 9, 12) 
    first_avg = get_cells_avg_color(img, first_cells) 
    print("First color average: blue {:0.2f}, green {:0.2f}, red {:0.2f}".format(*first_avg)) 

    second_cells = get_cells("A", "G", 5, 8) 
    second_avg = get_cells_avg_color(img, second_cells) 
    print("Second color average: blue {:0.2f}, green {:0.2f}, red {:0.2f}".format(*second_avg)) 

if __name__ == "__main__": 
    if len(sys.argv) == 2: 
     main(sys.argv[1]) 
    else: 
     print("Usage: python {} plate.jpg".format(__name__))