How to detect shape in Cytologique image python opencv

Question

I try to detect forms in cytology image and I get this result enter image description here my input image is enter image description here But My result does not see good can anyone help me ??? My stage was, Color image by (COLORMAP_HOT) Convert to grayscal image Apply the canny filter Find count Test the contour and i use python3.5 and opencv3

my code :

 #!/usr/bin/env python
 import cv2
import numpy as np
from pyimagesearch.shapedetector import ShapeDetector
import argparse
import imutils
from scipy import ndimage
import math
import matplotlib.pyplot as plt
 if __name__ == '__main__' :

im = cv2.imread("23.png")
#im_out = np.zeros((670, 543, 3), np.uint8);
#resized = imutils.resize(im, width=300)
#ratio = im.shape[0] / float(resized.shape[0])
#coloration
im_color = cv2.applyColorMap(im, cv2.COLORMAP_HOT)
imgg = im_color[:, :, 1]
#cv2.putText(im_color, colormap_name(k), (30, 180), cv2.FONT_HERSHEY_DUPLEX, 0.5, (255, 255, 255),1);
im_out = im_color
gray = cv2.cvtColor(im_color, cv2.COLOR_RGB2GRAY)

blurred = cv2.GaussianBlur(gray, (3, 3), 0)
canny = cv2.Canny(blurred, 120, 200)
kernel = np.ones((5,5),np.uint8)
#morph
dilation = cv2.dilate(canny,kernel,iterations = 1)
erosion = cv2.erode(dilation,kernel,iterations = 1)
dilation = cv2.dilate(erosion,kernel,iterations = 1)
erosion = cv2.erode(dilation,kernel,iterations = 1)    
blurred = cv2.GaussianBlur(erosion, (3, 3), 0)
canny = cv2.Canny(blurred, 200, 200)


cv2.imshow("dilation", dilation)
cv2.imshow("canny", canny)
cv2.imshow("erosion", erosion)
#(thresh, im_bw) = cv2.threshold(im_gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
cv2.imshow("im_out", im_out);
cv2.imshow("gray ", gray);



#contour
cnts = cv2.findContours(canny, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
# loop over the contours
for c in cnts:
    M = cv2.moments(c)
    if(M["m00"]==0):M["m00"]=1

    cX = int((M["m10"] / M["m00"]))
    cY = int((M["m01"] / M["m00"]))


    #shape = detect(c)
    c = c.astype("float")

    c = c.astype("int")
    #cv2.drawContours(im, [c], -1, (0, 255, 0), 2)
    #cv2.putText(im, shape, (cX, cY), cv2.FONT_HERSHEY_SIMPLEX,0.5, (255,0,0), 2)
    area = cv2.contourArea(c)
    perimeter = cv2.arcLength(c,True)
    M = cv2.moments(c)

    # initialize the shape name and approximate the contour
    shape = " "
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.05 * peri, True)
    (x, y, w, h) = cv2.boundingRect(approx)
    area = cv2.contourArea(c)
    radius = w/2
    if len(approx) == 3:
        shape = ""

    # if the shape has 4 vertices, it is either a square or
    # a rectangle
    elif len(approx) == 4:
        if (M['m00']==0):
           M['m00']=1
        cx = int(M['m10']/M['m00'])
        cy = int(M['m01']/M['m00'])
        # compute the bounding box of the contour and use the
        # bounding box to compute the aspect ratio
         #(x,y) be the top-left coordinate of the rectangle and (w,h) be its width and height.
        (x, y, w, h) = cv2.boundingRect(approx)
        print ("area",area,"perimeter",perimeter,"cx",cx,"cy",cy,"x",x,"y", y,"w", w, "h",h)
        #fichier.write("area",area,"perimeter",perimeter,"cx",cx,"cy",cy)
        print (sep="\n")
        ar = w / float(h)

        shape = "square" if ar >= 0.95 and ar <= 1.05 else "rectangle"
        cv2.drawContours(im, [c], -1, (255, 0, 0), 2)
        cv2.putText(im, shape, (cX, cY), cv2.FONT_HERSHEY_SIMPLEX,0.5, (255,0,0), 2)
    # if Cystine>6
    elif len(approx) == 6:
        if (M['m00']==0):
           M['m00']=1
        cx = int(M['m10']/M['m00'])
        cy = int(M['m01']/M['m00'])
        print ("area",area,"perimeter",perimeter,"cx",cx,"cy",cy)
        print (sep="\n")
        shape = "HEXA"

        cv2.drawContours(im, [c], -1, (255, 0, 0), 2)
        cv2.putText(im, shape, (cX, cY), cv2.FONT_HERSHEY_SIMPLEX,0.5, (255,0,0), 2)
    # otherwise, we assume the shape is a circle
    elif (abs(1 - (float(w)/h))<=2 and abs(1-(area/(math.pi*radius*radius)))<=0.2):
        if (M['m00']==0):
           M['m00']=1
        cx = int(M['m10']/M['m00'])
        cy = int(M['m01']/M['m00'])
        print ("area",area,"perimeter",perimeter,"cx",cx,"cy",cy)
        print (sep="\n")
        shape = "circle"
        cv2.drawContours(im, [c], -1, (255,0, 0), 2)
        cv2.putText(im, shape, (cX, cY), cv2.FONT_HERSHEY_SIMPLEX,0.5, (255,0, 0), 2)

# show the output image
    cv2.imshow("Image", im)



cv2.waitKey(0);