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run0.py
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## Important :
## directory strucrutre should be as follows
## root -> run0.py
# asl_alphabet_train --> asl_alphabet_train --> A
## B
## .
import cv2
import os
from hand_tracker import HandTracker
WINDOW = "Hand Tracking"
PALM_MODEL_PATH = "./palm_detection_without_custom_op.tflite"
LANDMARK_MODEL_PATH = "./hand_landmark.tflite"
ANCHORS_PATH = "./anchors.csv"
POINT_COLOR = (0, 255, 0)
CONNECTION_COLOR = (255, 0, 0)
THICKNESS = 2
from skimage.filters import threshold_yen
from skimage.exposure import rescale_intensity
# cv2.namedWindow(WINDOW)
# capture = cv2.VideoCapture(0)
#
# if capture.isOpened():
# hasFrame, frame = capture.read()
# else:
# hasFrame = False
# 8 12 16 20
# | | | |
# 7 11 15 19
# 4 | | | |
# | 6 10 14 18
# 3 | | | |
# | 5---9---13--17
# 2 \ /
# \ \ /
# 1 \ /
# \ \ /
# ------0-
connections = [
(0, 1), (1, 2), (2, 3), (3, 4),
(5, 6), (6, 7), (7, 8),
(9, 10), (10, 11), (11, 12),
(13, 14), (14, 15), (15, 16),
(17, 18), (18, 19), (19, 20),
(0, 5), (5, 9), (9, 13), (13, 17), (0, 17)
]
detector = HandTracker(
PALM_MODEL_PATH,
LANDMARK_MODEL_PATH,
ANCHORS_PATH,
box_shift=0.2,
box_enlarge=1.3
)
dir = 'asl_alphabet_train/asl_alphabet_train'
c = os.listdir(dir)
count = 0
pts=[]
lbs=[]
total=0
for j in c:
d = os.listdir(dir+'/'+j)
for i in d:
total = total +1
frame = cv2.imread(dir+'/'+j+'/'+i,1)
image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Some Image Pre-processing
yen_threshold = threshold_yen(image)
image = rescale_intensity(image, (0, yen_threshold), (0, 255))
points, _ = detector(image)
if points is not None:
count = count+1
print(count,end='')
print(' / ',end='')
print(total)
pts.append(points)
lbs.append(j)
for point in points:
x, y = point
cv2.circle(frame, (int(x), int(y)), THICKNESS * 2, POINT_COLOR, THICKNESS)
for connection in connections:
x0, y0 = points[connection[0]]
x1, y1 = points[connection[1]]
cv2.line(frame, (int(x0), int(y0)), (int(x1), int(y1)), CONNECTION_COLOR, THICKNESS)
# cv2.imshow('Output', frame)
# cv2.waitKey(0)
## Zipped together
dataset = list(zip(pts,lbs))
import pickle
## Dump the Dataset
with open('dataset.txt',wb) as fp:
pickle.dump(dataset,fp)
## To Load is Back :
## https://stackoverflow.com/questions/27745500/how-to-save-a-list-to-a-file-and-read-it-as-a-list-type
## https://stackoverflow.com/questions/2407398/how-to-merge-lists-into-a-list-of-tuples