dynamic_object_detector.py

import numpy as np
import cv2

class moving_detector:
    def __init__(self):
        a = 1

    def draw_flow(slef,img, flow, step=16):
        h, w = img.shape[:2]
        y, x = np.mgrid[step / 2:h:step, step / 2:w:step].reshape(2, -1)
        fx, fy = flow[y, x].T
        lines = np.vstack([x, y, x + fx, y + fy]).T.reshape(-1, 2, 2)
        lines = np.int32(lines + 0.5)
        vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
        cv2.polylines(vis, lines, 0, (0, 255, 0))
        for (x1, y1), (x2, y2) in lines:
            cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
        return vis

    def warp_flow(self,img, flow):
        h, w = flow.shape[:2]
        flow = -flow
        flow[:, :, 0] += np.arange(w)
        flow[:, :, 1] += np.arange(h)[:, np.newaxis]
        res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
        return res

    def draw_hsv(self,flow):
        h, w = flow.shape[:2]
        fx, fy = flow[:, :, 0], flow[:, :, 1]
        ang = np.arctan2(fy, fx) + np.pi
        v = np.sqrt(fx * fx + fy * fy)
        hsv = np.zeros((h, w, 3), np.uint8)
        hsv[..., 0] = ang * (180 / np.pi / 2)
        hsv[..., 1] = 255
        hsv[..., 2] = np.minimum(v * 4, 255)
        bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
        return bgr

    def show_flow (self,prev,cur):

        prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)
        img = cur
        vis = img.copy()
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        # apply color mask here
        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 5, 15, 3, 5, 1.1, cv2.OPTFLOW_FARNEBACK_GAUSSIAN)
        flow_img = self.draw_flow(gray, flow)
        gray1 = cv2.cvtColor(self.draw_hsv(flow), cv2.COLOR_BGR2GRAY)
        thresh = cv2.threshold(gray1, 25, 255, cv2.THRESH_BINARY)[1]
        thresh = cv2.dilate(thresh, None, iterations=2)
        (cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

        # loop over the contours
        for c in cnts:
            # if the contour is too small, ignore it
            # modify parameters for detecting close objects.
            (x, y, w, h) = cv2.boundingRect(c)
            if w > 100 and h > 100 and w < 200 and h < 300:
                cv2.rectangle(vis, (x, y), (x + w, y + h), (0, 0, 255), 4)

        return (flow_img,vis)