代码拉取完成,页面将自动刷新
同步操作将从 LiJiayi96/DJI_Image_yolo 强制同步,此操作会覆盖自 Fork 仓库以来所做的任何修改,且无法恢复!!!
确定后同步将在后台操作,完成时将刷新页面,请耐心等待。
from ctypes import *
import math
import random
import os
import cv2
import numpy as np
import time
import darknet
netMain = None
metaMain = None
altNames = None
def load_data():
global metaMain, netMain, altNames
configPath = "./cfg/yolov3.cfg"
weightPath = "./yolo-weights/yolov3.weights"
metaPath = "./cfg/coco.data"
if not os.path.exists(configPath):
raise ValueError("Invalid config path `" +
os.path.abspath(configPath) + "`")
if not os.path.exists(weightPath):
raise ValueError("Invalid weight path `" +
os.path.abspath(weightPath) + "`")
if not os.path.exists(metaPath):
raise ValueError("Invalid data file path `" +
os.path.abspath(metaPath) + "`")
if netMain is None:
netMain = darknet.load_net_custom(configPath.encode(
"ascii"), weightPath.encode("ascii"), 0, 1) # batch size = 1
if metaMain is None:
metaMain = darknet.load_meta(metaPath.encode("ascii"))
if altNames is None:
try:
with open(metaPath) as metaFH:
metaContents = metaFH.read()
import re
match = re.search("names *= *(.*)$", metaContents,
re.IGNORECASE | re.MULTILINE)
if match:
result = match.group(1)
else:
result = None
try:
if os.path.exists(result):
with open(result) as namesFH:
namesList = namesFH.read().strip().split("\n")
altNames = [x.strip() for x in namesList]
except TypeError:
pass
except Exception:
pass
def convertBack(x, y, w, h):
xmin = int(round(x - (w / 2)))
xmax = int(round(x + (w / 2)))
ymin = int(round(y - (h / 2)))
ymax = int(round(y + (h / 2)))
return xmin, ymin, xmax, ymax
def cvDrawBoxes(detections, img):
total_info = []
for detection in detections:
x, y, w, h = detection[2][0],\
detection[2][1],\
detection[2][2],\
detection[2][3]
xmin, ymin, xmax, ymax = convertBack(
float(x), float(y), float(w), float(h))
pt1 = (xmin, ymin)
pt2 = (xmax, ymax)
cv2.rectangle(img, pt1, pt2, (0, 255, 0), 1)
cv2.putText(img,
detection[0].decode() +
" [" + str(round(detection[1] * 100, 2)) + "]",
(pt1[0], pt1[1] - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
[0, 255, 0], 2)
total_info.append((detection[0].decode(),detection[1] * 100,[xmin, ymin, xmax, ymax]))
return img,total_info
def YOLO():
load_data()
cap = cv2.VideoCapture("ccani.mp4")
cap.set(3, 1280)
cap.set(4, 720)
print("Starting the YOLO loop...")
# Create an image we reuse for each detect
darknet_image = darknet.make_image(darknet.network_width(netMain),
darknet.network_height(netMain),3)
while True:
prev_time = time.time()
ret, frame_read = cap.read()
frame_rgb = cv2.cvtColor(frame_read, cv2.COLOR_BGR2RGB)
frame_resized = cv2.resize(frame_rgb,
(darknet.network_width(netMain),#416
darknet.network_height(netMain)),#416
interpolation=cv2.INTER_LINEAR)
darknet.copy_image_from_bytes(darknet_image,frame_resized.tobytes())
detections = darknet.detect_image(netMain, metaMain, darknet_image, thresh=0.50) #thresh=0.50识别的阈值
#detections= (b'bird', 0.9903159141540527, (172.501708984375, 188.70071411132812, 56.11371994018555, 177.9843292236328))
# nameTag, dets[j].prob[i], (b.x, b.y, b.w, b.h)
# for i in range(len(detections)):
# print('detections= ',detections[i])
image ,total_info= cvDrawBoxes(detections, frame_resized) #total_info [name ,pro,[左上,右下]]
print('total_info=',total_info)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
print('fps=',1/(time.time()-prev_time))
cv2.imshow('Demo', image)
cv2.waitKey(3)
cap.release()
if __name__ == "__main__":
YOLO()
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