Skip to content

Import the necessary library modules #3

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
adhya11720 wants to merge 4 commits into
base: master
Choose a base branch
from
Open

Import the necessary library modules #3

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
9821fc6
Import the necessary library modules
adhya11720 Dec 4, 2020
28bf99e
requirements.txt file added
adhya11720 Dec 4, 2020
7de5556
Load the COCO class labels
adhya11720 Dec 4, 2020
ca02087
Check if we are going to use GPU
adhya11720 Dec 4, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions requirements.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1 @@

26 changes: 26 additions & 0 deletions social_distance_detector.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1 +1,27 @@
from pyimagesearch import social_distancing_config as config
from pyimagesearch.detection import detect_people
from scipy.spatial import distance as dist
import numpy as np
import argparse
import imutils
import cv2
import os


#Load the COCO class labels on which YOLO model will be trained on
labelsPath = os.path.sep.join([config.MODEL_PATH, "coco.names"])
LABELS = open(labelsPath).read().strip().split("\n")


weightsPath = os.path.sep.join([config.MODEL_PATH, "yolov3.weights"])
configPath = os.path.sep.join([config.MODEL_PATH, "yolov3.cfg"])

print("[INFO] loading YOLO from disk...")
net = cv2.dnn.readNetFromDarknet(configPath, weightsPath)

#Check if we are going to use GPU
if config.USE_GPU:

print("[INFO] setting preferable backend and target to CUDA...")
net.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA)
net.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA)