Process image from webcam in colab
Project description
Author:KuoYuan Li
wrap the javascript code to handle image from webcam in colab
本package提供一系列在 colab 中操作webcam的方法
在colab中使用之前請先進行安裝
!pip install colabcam
webcam 拍照存檔
(take a photo from webcam and save to 1.jpg)
import colabcam
colabcam.take_photo("1.jpg")
動態顯示人臉框及文字(cv2只支援英數字)
(demo with mediapipe face_detection)
#Note:bbox(人臉框)是另外疊加顯示的,速度會有延遲是正常的
import mediapipe as mp
import colabcam
import numpy as np
import cv2
mp_face_detection = mp.solutions.face_detection
face_detection = mp_face_detection.FaceDetection()
# start streaming video from webcam
colabcam.video_stream()
# label for video
label_html = '顯示中...(點擊畫面以結束顯示)'
# initialze bounding box to empty
bbox = ''
while True:
js_reply = colabcam.video_frame(label_html, bbox)
if not js_reply:break
# convert JS response to OpenCV Image
img = colabcam.js_to_image(js_reply["img"])
results = face_detection.process(img)
frame_height,frame_width=np.shape(img)[0:2]
overlapImg = np.zeros([frame_height,frame_width,4], dtype=np.uint8)
if results.detections:
for detection in results.detections:
box = detection.location_data.relative_bounding_box
x, y, w, h =int(box.xmin*frame_width),int(box.ymin*frame_height), \
int(box.width*frame_width),int(box.height*frame_height)
if w>0 and h>0:
overlapImg = cv2.rectangle(overlapImg,(x,y),(x+w,y+h),(255,0,0),2)
cv2.putText(overlapImg,'text test',(x,y-20),cv2.FONT_HERSHEY_SIMPLEX,1,(255,0,0),2)
bbox = colabcam.cvImg2bbox(overlapImg)
License
MIT
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
colabcam-1.0.3.tar.gz
(5.4 kB
view details)
File details
Details for the file colabcam-1.0.3.tar.gz
.
File metadata
- Download URL: colabcam-1.0.3.tar.gz
- Upload date:
- Size: 5.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.8
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 18ab3e407bf23bd0c044a45dd5010191b2551b40d57ede1ccbff65365026e1d6 |
|
MD5 | 9615ecab230b2a14ec176abb9b1dd1d3 |
|
BLAKE2b-256 | 4c40825fa07131d01c42078c314f0b87006ab1e231e8aa946e6ec3f86cef1cd0 |