Update for training

Edmond Yoo

2018-09-14 8eb0d400e80f3dd135313834ce103bd0f9e62dbc

 darknet.py

@@ -31,6 +31,7 @@
import math
import random
import os
import cv2

def sample(probs):
    s = sum(probs)
@@ -224,7 +225,9 @@
    #pylint: disable= C0321
    im = load_image(image, 0, 0)
    #import cv2
    #custom_image = cv2.imread(image) # use: detect(,,imagePath,)
    #custom_image_bgr = cv2.imread(image) # use: detect(,,imagePath,)
    #custom_image = cv2.cvtColor(custom_image_bgr, cv2.COLOR_BGR2RGB)
    #custom_image = cv2.resize(custom_image,(lib.network_width(net), lib.network_height(net)), interpolation = cv2.INTER_LINEAR)
    #import scipy.misc
    #custom_image = scipy.misc.imread(image)
    #im, arr = array_to_image(custom_image)     # you should comment line below: free_image(im)
@@ -235,7 +238,8 @@
    if debug: print("Assigned pnum")
    predict_image(net, im)
    if debug: print("did prediction")
    dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, None, 0, pnum, 1)
    #dets = get_network_boxes(net, custom_image_bgr.shape[1], custom_image_bgr.shape[0], thresh, hier_thresh, None, 0, pnum, 0) # OpenCV
    dets = get_network_boxes(net, im.w, im.h, thresh, hier_thresh, None, 0, pnum, 0)
    if debug: print("Got dets")
    num = pnum[0]
    if debug: print("got zeroth index of pnum")
@@ -362,6 +366,7 @@
    if not os.path.exists(imagePath):
        raise ValueError("Invalid image path `"+os.path.abspath(imagePath)+"`")
    # Do the detection
    #detections = detect(netMain, metaMain, imagePath, thresh) # if is used cv2.imread(image)
    detections = detect(netMain, metaMain, imagePath.encode("ascii"), thresh)
    if showImage:
        try:
@@ -417,5 +422,49 @@
            print("Unable to show image: "+str(e))
    return detections


def capture(thresh=.5, hier_thresh=.5, nms=.45, configPath="./cfg/yolov3.cfg", weightPath="yolov3.weights",
            metaPath="./data/coco.data", showImage=True, makeImageOnly=False, initOnly=False):
    global metaMain, netMain, altNames  # pylint: disable=W0603
    netMain = load_net_custom(configPath.encode("ascii"), weightPath.encode("ascii"), 0, 1)  # batch size = 1
    metaMain = load_meta(metaPath.encode("ascii"))

    num = c_int(0)
    pnum = pointer(num)
    num = pnum[0]

    capture = cv2.VideoCapture('../data/test3.mp4')
    print(capture.get(cv2.CAP_PROP_FPS))

    capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1024)
    capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 768)

    while True:
        ret, frame = capture.read()
        im, arr = array_to_image(frame)
        predict_image(netMain, im)
        dets = get_network_boxes(netMain, im.w, im.h, thresh, hier_thresh, None, 0, pnum, 1)
        if nms:
            do_nms_sort(dets, num, metaMain.classes, nms)
        res = []
        for j in range(num):
            for i in range(metaMain.classes):
                if dets[j].prob[i] > 0:
                    b = dets[j].bbox
                    nameTag = metaMain.names[i]
                    res.append((nameTag, dets[j].prob[i], (b.x, b.y, b.w, b.h)))
        print(res)
        cv2.imshow('frame', frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    capture.release()
    cv2.destroyAllWindows()


if __name__ == "__main__":
    print(performDetect())
    performDetect(imagePath="../data/test1.jpg", thresh=0.25, configPath="./cfg/tiny_yolo.cfg",
                  weightPath="./weights/second_general/tiny_yolo_17000.weights",
                  metaPath="./data/obj.data", showImage=True, makeImageOnly=False, initOnly=False)
    #print(performDetect(showImage=False))
    #capture()