记录点滴

• 非极大抑制

import numpy as np
from numpy import *

# boxes is a list of size (n x 5) (x1, y1, x2, y2, score)
# trial is a numpy array of size (n x 5)

def nms (boxes,overlap):
  if not boxes:
        pick = []
    else:
        trial = zeros((len(boxes),5),dtype=float64)
        trial[:] = boxes[:]
        x1 = trial[:,0]
        y1 = trial[:,1]
        x2 = trial[:,2]
        y2 = trial[:,3]
        score = trial[:,4]
        area = (x2-x1+1)*(y2-y1+1)
    
        #vals = sort(score)
        I = argsort(score)  # sort by score, from the smallest to biggest
        pick = []
        count = 1
        while (I.size!=0):
            #print "Iteration:",count
            last = I.size
            i = I[last-1]
            pick.append(i)
            suppress = [last-1]
            for pos in range(last-1):
                j = I[pos]
                xx1 = max(x1[i],x1[j])
                yy1 = max(y1[i],y1[j])
                xx2 = min(x2[i],x2[j])
                yy2 = min(y2[i],y2[j])
                w = xx2-xx1+1
                h = yy2-yy1+1
                if (w>0 and h>0):
                    o = w*h/area[j]
                    print "Overlap is",o
                    if (o >overlap):
                        suppress.append(pos)
            I = delete(I,suppress)
            count = count + 1
return pick

• 根据图片中物体颜色实现物体分割

from moviepy.editor import VideoFileClip
import cv2
import numpy as np
import os
def process_1(img):
    mask = cv2.inRange(img, (36, 0, 0), (70, 255,255))
    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)))
    mask = cv2.Canny(mask, 100, 300)
    mask = cv2.GaussianBlur(mask, (1, 1), 0)
    mask = cv2.Canny(mask, 100, 300)
    im2, cnts, hierarchy = cv2.findContours(mask.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
    cnts = sorted(cnts, key = cv2.contourArea, reverse = True)[:5]
    cv2.drawContours(img, cnts, -1, (0,255,0), 3)
    return img

def process_2(img):
    mask = cv2.inRange(img, (36, 0, 0), (70, 255,255))
    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)))
    mask = cv2.Canny(mask, 100, 300)
    mask = cv2.GaussianBlur(mask, (1, 1), 0)
    mask = cv2.Canny(mask, 100, 300)
    im2, cnts, hierarchy = cv2.findContours(mask.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
    cnts = sorted(cnts, key = cv2.contourArea, reverse = True)[:5]
    rects = []
    for c in cnts:
        peri = cv2.arcLength(c, True)
        approx = cv2.approxPolyDP(c, 0.02 * peri, True)
        x, y, w, h = cv2.boundingRect(approx)
        if h >= 15:
            # if height is enough
            # create rectangle for bounding
            rect = (x, y, w, h)
            rects.append(rect)
            cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 1)# get largest five contour area
    ## slice the green
    imask = mask>0
    green = np.zeros_like(img, np.uint8)
    green[imask] = img[imask]
    return img

cap = cv2.VideoCapture('./greenObject.mp4',0)
while(cap.isOpened()):
    ret, frame = cap.read()
    if ret is True:
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        im_process = process_{optional}(hsv)
    #     x, y, w, h = cv2.findNonZero(im_process)
        im_process = cv2.cvtColor(im_process, cv2.COLOR_HSV2BGR)
        cv2.imshow('frame',im_process)
    if cv2.waitKey(1) & 0xFF == ord('q'):
            break
cap.release()
cv2.destroyAllWindows()