A Thai sign language translator library used with Mediapipe that translate Thai hand sign language into plain Thai characters.
Project description
Thai sign language translator (ThSLT)
Description
This is a Thai sign language library for python used for translating Thai sign language into plain Thai characters. This library is used with Mediapipe and OpenCV, so you should install those libraries first to make ThSLT function properly. Although the code works about 90% of the time, there are a lot of factors that you need to consider such as background , lighting , camera quality , hardware qualities. To increase the accuracy, you can adjust the min_tracking_confidence and min_detection_confidence from the default values.
Table of Contents
Installation
Use the following methods to install nessecary libraries
- To install OpenCV, use the following command
pip install opencv-python
- To install Mediapipe, use the following command
pip install mediapipe
Use the following method to install ThSLT
- To install ThSLT, use the following command
pip install thslt==1.0.2
Usage
Here's an example setup for ThSLT:
import thslt , cv2
import mediapipe as mp
mpdraw = mp.solutions.drawing_utils
mphands = mp.solutions.hands
mpdrawing_styles = mp.solutions.drawing_styles
hands = mphands.Hands(static_image_mode=False,
model_complexity=1,
min_detection_confidence=0.8,
min_tracking_confidence=0.8,
max_num_hands=2)
capture = cv2.VideoCapture(0)
text_encode = []
while True:
ret, frame = capture.read()
bgrtorgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
results = hands.process(bgrtorgb)
thslt.translate(frame,results,text_encode)
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
for id, lm in enumerate(hand_landmarks.landmark):
h,w,c = frame.shape
Cx,Cy = int(lm.x*w), int(lm.y*h)
mpdraw.draw_landmarks(frame,
hand_landmarks,
mphands.HAND_CONNECTIONS,
mpdrawing_styles.get_default_hand_landmarks_style(),
mpdrawing_styles.get_default_hand_connections_style())
cv2.imshow("Hand Tracking",frame)
key = cv2.waitKey(1)
if key == 27: ### Esc key
break
cv2.destroyAllWindows()
translation = thslt.decode(text_encode)
print(translation)
ThSLT has a built in Mediapipe hand mapping. So mapping the hand landmarks is not necessary. It only helps you notice that the camera is actually mapping your hand.
Configuration
Text_encode
- declare text_encode as a blank array before start capturing the video
text_encode = []
Features
Translate
- use this function after you create a loop for OpenCV
translate(frame,handlabel,results,text_encode)
- frame = capture.read()
- results = Hands.process(bgrtorgb)
- text_encode = [ ]
Decode
- use this function after you exit the loop for OpenCV to encode text_encode
translation = encode(text_encode)
Documentation
The document is not finished yet.
License
Copyright 2023 Papangkon Ninarundech
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Support
Contact +66 097-153-3812 for more information
Acknowledgments
Thank you to the individuals who assisted in creating this project.
- Mr.Jiraroj Wiruchpongsanon
Project details
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