def map_time_step(img_path,
rpm=19.6,
field=14,
diameter=70,
suffix=".bmp",
save_path=None):
img_list = sorted(gb.glob(img_path + r"/*" + suffix), key=os.path.getmtime)
pvoc = PascalVocXmlParser()
# Get the linear velocity of the rotating cloth
perimeter = np.pi * diameter
min_velo = rpm * perimeter
speed = min_velo / 60.0
for i in range(1, len(img_list), 1):
img_file = img_list[i]
print(img_file)
ann_file = get_ann_file(img_file)
if os.path.isfile(ann_file):
boxes = pvoc.get_boxes(ann_file)
else:
boxes = []
pre_img_file = img_list[i - 1]
pre_ann_file = get_ann_file(pre_img_file)
if os.path.isfile(pre_ann_file):
pre_boxes = pvoc.get_boxes(pre_ann_file)
else:
pre_boxes = []
img = cv2.imread(img_file, cv2.IMREAD_COLOR)
img_h, img_w = img.shape[:2]
intv = get_time_interval(img_file, pre_img_file)
nboxes = map_next_boxes(pre_boxes, speed, intv, field, (img_h, img_w))
#print(boxes)
#print(nboxes)
img = draw_boxes(img, boxes, color=(0, 0, 255))
img = draw_boxes(img, nboxes, color=(255, 0, 0))
if save_path is not None:
_, filename = os.path.split(img_file)
cv2.imwrite(os.path.join(save_path, filename), img)
else:
cv2.imshow("image", img)
cv2.waitKey(0)
import os, sys
import numpy as np
import glob as gb
import xml.etree.ElementTree as ET
from sklearn.cluster import KMeans
from matplotlib import pyplot as plt
from PascalVocParser import PascalVocXmlParser
pvoc = PascalVocXmlParser()
def show_histogram(path):
dataset = encode_dataset(path)
widths = dataset[:, 0]
heights = dataset[:, 1]
plt.subplot(1, 2, 1), plt.hist(widths), plt.title("Width Distribution")
plt.subplot(1, 2, 2), plt.hist(heights), plt.title("Heights Distribution")
plt.show()
def cluster_anchors(path, k=6, label=None):
dataset = encode_dataset(path, label=label)
km = KMeans(n_clusters=k, random_state=9).fit(dataset)
ac = np.array(km.cluster_centers_, dtype=np.int32)
return ac
def encode_dataset(path, label=None):
dataset = [] # dataset that x_length larger than x_thres
for xml_file in gb.glob(path + r"/*.xml"):
def __init__(self, params):
self.pvoc = PascalVocXmlParser()
self.updateParams(params)