-
Notifications
You must be signed in to change notification settings - Fork 0
/
reaadme.txt
33 lines (19 loc) · 911 Bytes
/
reaadme.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
by using this api we can detect any object detection using yolo3.
we have only these 3 things requirement ---->
1.Pretrained weights file (__name__.weights)
2.classes names file (_name_.names)
3.yolov3_custum.cfg (_name_.cfg)
in yolo_detection.py
---change to locations---->
#Give the configuration and weight files for the model and load the network using them.
1.modelConfiguration = "yolov3_custom.cfg";
2.modelWeights = "yolov3.weights";
# Load names of classes
3.classesFile = "coco.names";
yolov3_custom.cfg
1.subdivisons=16/32
2.max_batches=(classes*2000) not less than 4000 (max_batches = 500200)
3.steps=80% of max_batches,90% of max_batches (ex.if steps=4000 then steps=3200,3600 if classes=1) (steps=400000,450000 if classes =80) or on 17 line
search yolo
4.filters=(classes+5)*3 filters (85*3)=255
classes=80