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test_video.py
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test_video.py
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# -*- coding: utf-8 -*-
"""
Created on Sat Jun 13 19:00:40 2020
@author: dell
"""
from keras.models import load_model
from PIL import Image
import numpy as np
from matplotlib import pyplot as plt
import cv2
import time, os
os.chdir(r"C:\Users\dell\Desktop\Facial KeyPoint detection")
model = load_model('./model1.h5') # <-- Saved model path
# input video file path
input_file = 'sample.mp4'
# output file path
output_filename = 'sample_out.avi'
def get_points_main(img):
def detect_points(face_img):
me = np.array(face_img)/255
x_test = np.expand_dims(me, axis=0)
x_test = np.expand_dims(x_test, axis=3)
y_test = model.predict(x_test)
label_points = (np.squeeze(y_test)*48)+48
return label_points
# load haarcascade
face_cascade = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml')
dimensions = (96, 96)
try:
default_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
gray_img = cv2.cvtColor(default_img, cv2.COLOR_RGB2GRAY)
faces = face_cascade.detectMultiScale(gray_img, 1.3, 5)
# faces = face_cascade.detectMultiScale(gray_img, 4, 6)
except:
return []
faces_img = np.copy(gray_img)
plt.rcParams["axes.grid"] = False
all_x_cords = []
all_y_cords = []
for i, (x,y,w,h) in enumerate(faces):
h += 10
w += 10
x -= 5
y -= 5
try:
just_face = cv2.resize(gray_img[y:y+h,x:x+w], dimensions)
except:
return []
cv2.rectangle(faces_img,(x,y),(x+w,y+h),(255,0,0),1)
scale_val_x = w/96
scale_val_y = h/96
label_point = detect_points(just_face)
all_x_cords.append((label_point[::2]*scale_val_x)+x)
all_y_cords.append((label_point[1::2]*scale_val_y)+y)
final_points_list = []
try:
for ii in range(len(all_x_cords)):
for a_x, a_y in zip(all_x_cords[ii], all_y_cords[ii]):
final_points_list.append([a_x, a_y])
except:
return final_points_list
return final_points_list
# cap = cv2.VideoCapture(0)
cap = cv2.VideoCapture(input_file)
ret, frame = cap.read()
height, width, channel = frame.shape
fourcc = cv2.VideoWriter_fourcc(*'MJPG')
out = cv2.VideoWriter(output_filename, fourcc, 20.0, (width, height))
frame_no = 0
while cap.isOpened():
a = time.time()
frame_no += 1
ret, frame = cap.read()
if frame_no > 75*30:
break
if frame_no in range(60*30, 75*30):
points = get_points_main(frame)
try:
overlay = frame.copy()
except Exception as e:
print(e)
break
for point in points:
cv2.circle(frame, tuple(point), 3, (255, 255, 255), -1)
# cv2.line(frame, last_point, tuple(point), (0,0,255), thickness=1)
# cv2.putText(overlay, str(i), tuple(point), 1, 1, (255, 255, 255))
if len(points) != 0:
o_line_points = [[12,13], [13,11], [11,14], [14,12], [12,10], [11,10], [10,3], [12,5], [11,3], [10,5], [10,4], [10,2], [5,1], [1,4], [2,0], [0,3], [5,9], [9,8], [8,4], [2,6], [6,7], [7,3]]
num_face = len(points)//15
for i in range(num_face):
line_points = np.array(o_line_points) + (15*(i))
the_color = (189, 195, 199)
for ii in line_points:
cv2.line(overlay, tuple(points[ii[0]]), tuple(points[ii[1]]), the_color, thickness=1)
opacity = 0.3
cv2.addWeighted(overlay, opacity, frame, 1 - opacity, 0, frame)
out.write(frame)
# cv2.imshow('frame',frame)
b = time.time()
print(str((b-a)))
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()