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提交demo.py

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V0.1.0
jiangxt 2 years ago
parent f0ee9320c4
commit 3c3737c667
2 changed files with 163 additions and 75 deletions
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89
tool/demo.py
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@ -0,0 +1,89 @@
from PP_TSMv2_infer import *
from mediapipe_detection import mediapipe_detect
import mediapipe as mp
import cv2
mp_holistic = mp.solutions.holistic
def main(input_path,output_path, face_b, left_hand_b, right_hand_b):
cap = cv2.VideoCapture(input_path)
config = 'D:/download/PaddleVideo1/output/output/pptsm_lcnet_k400_16frames_uniform.yaml'
model_file = 'D:/download/PaddleVideo1/output/output/ppTSMv2.pdmodel' # 推理模型存放地址
params_file = 'D:/download/PaddleVideo1/output/output/ppTSMv2.pdiparams' # 推理模型参数存放地址
batch_size = 1 # 输出推理模型
infer,predictor = PP_TSMv2_predict().create_inference_model(config,model_file,params_file)
res = PP_TSMv2_predict().predict(config, input_path, batch_size, predictor,infer)
label = res["topk_class"]
if label == 0:
label = "Nodding!"
elif label == 1:
label = "not playing phone!"
elif label == 2:
label = "not sleep!"
elif label == 3:
label = "playing phone!"
elif label == 4:
label = "sleep!"
else:
pass
fps_video = cap.get(cv2.CAP_PROP_FPS)
frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
codec = cv2.VideoWriter_fourcc(*'XVID')
video_name = os.path.basename(input_path)
out = cv2.VideoWriter(output_path + "/" + video_name, codec, fps_video, (frame_width, frame_height))
with mp_holistic.Holistic(model_complexity=2,min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:
while True:
ret, frame = cap.read()
if not ret:
break
image, results = mediapipe_detect().mediapipe_detection(frame, holistic)
cv2.namedWindow("mediapipe_detections", cv2.WINDOW_AUTOSIZE)
if label == "Nodding!":
image, res = mediapipe_detect().get_bbox(image, results, face_b, left_hand_b, right_hand_b,label)
cv2.putText(image, "the person's head is " + label, (0, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0),
1)
elif label == "sleep!":
image, res = mediapipe_detect().get_bbox(image, results, face_b, left_hand_b, right_hand_b,label)
cv2.putText(image, "the person is " + label, (0, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0),
1)
elif label == "not sleep!":
image, res = mediapipe_detect().get_bbox(image, results, face_b, left_hand_b, right_hand_b,label)
cv2.putText(image, "the person is " + label, (0, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0),
1)
elif label == "playing phone!":
image, res = mediapipe_detect().get_bbox(image, results, face_b, left_hand_b, right_hand_b,label)
cv2.putText(image, "the person'hand is " + label, (0, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0),
1)
elif label == "not playing phone!":
image, res = mediapipe_detect().get_bbox(image, results, face_b, left_hand_b, right_hand_b,label)
cv2.putText(image, "the person'hand is " + label, (0, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0),
1)
cv2.imshow("mediapipe_detections", image)
out.write(image)
if cv2.waitKey(10) & 0xFF == ord('q'):
break
out.write(image)
# print(res)
cap.release()
out.release()
cv2.destroyAllWindows()
if __name__=="__main__":
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-1_0_1.avi'
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-1_398_1.avi'
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-1_597_0.avi' #正例
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-1_597_1.avi'
input = 'D:/download/PaddleVideo1/output/output/after_1/0711-1_796_0.avi' #正例，推理成功
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-1_796_1.avi'
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-3_0_0.avi'
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-3_1400_0.avi'
output = "D:/download/PaddleVideo1/output/output1"
face_b = 50
left_hand_b = 7
right_hand_b = 7
main(input,output,face_b,left_hand_b,right_hand_b)

149
tool/mediapipe_detection.py
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@ -7,7 +7,6 @@ import numpy as np
from mediapipe.framework.formats import landmark_pb2
import os
mp_holistic = mp.solutions.holistic
_PRESENCE_THRESHOLD = 0.5
@ -53,15 +52,15 @@ def _normalized_to_pixel_coordinates(
x_px = min(math.floor(normalized_x * image_width), image_width - 1)
y_px = min(math.floor(normalized_y * image_height), image_height - 1)
# return print("转化的真实坐标：",x_px, y_px)
return x_px,y_px
return x_px, y_px
def draw_landmarks(
image: np.ndarray,
landmark_list: landmark_pb2.NormalizedLandmarkList,
connections: Optional[List[Tuple[int, int]]] = None,
landmark_drawing_spec: Union[DrawingSpec,Mapping[int, DrawingSpec]] = DrawingSpec(color=RED_COLOR),
connection_drawing_spec: Union[DrawingSpec, Mapping[Tuple[int, int],DrawingSpec]] = DrawingSpec()):
image: np.ndarray,
landmark_list: landmark_pb2.NormalizedLandmarkList,
connections: Optional[List[Tuple[int, int]]] = None,
landmark_drawing_spec: Union[DrawingSpec, Mapping[int, DrawingSpec]] = DrawingSpec(color=RED_COLOR),
connection_drawing_spec: Union[DrawingSpec, Mapping[Tuple[int, int], DrawingSpec]] = DrawingSpec()):
"""
主要是绘制关键点的连接图
image:输入的数据
@ -81,7 +80,7 @@ def draw_landmarks(
(landmark.HasField('presence') and
landmark.presence < _PRESENCE_THRESHOLD)):
continue
landmark_px = _normalized_to_pixel_coordinates(landmark.x, landmark.y, #将归一化坐标值转换为图像坐标值
landmark_px = _normalized_to_pixel_coordinates(landmark.x, landmark.y, # 将归一化坐标值转换为图像坐标值
image_cols, image_rows)
# print('图像像素坐标:',landmark_px)
if landmark_px:
@ -90,7 +89,7 @@ def draw_landmarks(
dot_list = []
if connections:
# num_landmarks = len(landmark_list.landmark)
#connections:keypoint索引元组的列表，用于指定如何在图形中连接地标。
# connections:keypoint索引元组的列表，用于指定如何在图形中连接地标。
# Draws the connections if the start and end landmarks are both visible.
starts = []
@ -139,7 +138,7 @@ def draw_landmarks(
class mediapipe_detect:
def mediapipe_detection(self,image, model):
def mediapipe_detection(self, image, model):
"""
mediapipe检测模块
image：输入数据集
@ -152,7 +151,7 @@ class mediapipe_detect:
# image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) # COLOR COVERSION RGB 2 BGR
return image, results
def Drawing_bbox(self,result,bias):
def Drawing_bbox(self, result, bias):
'''
根据关键点坐标，获取最大外接矩形的坐标点
@ -163,15 +162,14 @@ class mediapipe_detect:
result = np.array(result)
b = bias
if result.any():
rect = cv2.boundingRect(result) #返回值, 左上角的坐标[x,y, w,h]
rect = cv2.boundingRect(result) # 返回值, 左上角的坐标[x,y, w,h]
bbox = [[rect[0] - b, rect[1] - b], [rect[0] + rect[2] + b, rect[1] - b],
[rect[0] - b, rect[1] + rect[3] + b], [rect[0] + rect[2] + b, rect[1] + rect[3] + b]] #四个角的坐标
[rect[0] - b, rect[1] + rect[3] + b], [rect[0] + rect[2] + b, rect[1] + rect[3] + b]] # 四个角的坐标
return bbox
def get_bbox(self,image,results,face_b,left_hand_b,right_hand_b):
def get_bbox(self, image, results, face_b, left_hand_b, right_hand_b, label):
'''
主要是根据关键点坐标，绘制矩形框
@ -181,7 +179,7 @@ class mediapipe_detect:
image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
h,w,g = image.shape
h, w, g = image.shape
# print("h:",h,"w:",w,"g:",g)
"""获取头部、手部关键点"""
@ -210,9 +208,15 @@ class mediapipe_detect:
)
"""根据关键点的坐标绘制最大外接矩形"""
fl_bbox = self.Drawing_bbox(face_location,face_b)
lh_bbox = self.Drawing_bbox(left_hand_location,left_hand_b)
rh_bbox = self.Drawing_bbox(right_hand_location,right_hand_b)
fl_bbox = self.Drawing_bbox(face_location, face_b)
lh_bbox = self.Drawing_bbox(left_hand_location, left_hand_b)
rh_bbox = self.Drawing_bbox(right_hand_location, right_hand_b)
if label == "Nodding" or label == "sleep!" or label == "not playing phone!":
lh_bbox = None
rh_bbox = None
elif label == "not sleep!" or label == "playing phone!":
fl_bbox = None
"""调整头部检测框的大小"""
if fl_bbox is not None:
@ -222,34 +226,34 @@ class mediapipe_detect:
fl_bbox[0][0] = fl_bbox[0][0] + 30
fl_bbox[0][1] = fl_bbox[0][1] + 5
# print(fl_bbox)
for i in range(0,4):
for j in range(0,2):
for i in range(0, 4):
for j in range(0, 2):
if fl_bbox[i][j] < 0:
fl_bbox[i][j] = 0
elif fl_bbox[i][0] > w:
fl_bbox[i][0] = w
elif fl_bbox[i][1] > h :
elif fl_bbox[i][1] > h:
fl_bbox[i][1] = h
else:
pass
cv2.rectangle(image, fl_bbox[0], fl_bbox[3],DrawingSpec.color, DrawingSpec.thickness)
cv2.rectangle(image, fl_bbox[0], fl_bbox[3], DrawingSpec.color, DrawingSpec.thickness)
if lh_bbox is not None:
for i in range(0,4):
for j in range(0,2):
for i in range(0, 4):
for j in range(0, 2):
if lh_bbox[i][j] < 0:
lh_bbox[i][j] = 0
elif lh_bbox[i][0] > w:
lh_bbox[i][0] = w
elif lh_bbox[i][1] > h :
elif lh_bbox[i][1] > h:
lh_bbox[i][1] = h
else:
pass
cv2.rectangle(image, lh_bbox[0], lh_bbox[3],DrawingSpec.color, DrawingSpec.thickness)
cv2.rectangle(image, lh_bbox[0], lh_bbox[3], DrawingSpec.color, DrawingSpec.thickness)
if rh_bbox is not None:
for i in range(0,4):
for j in range(0,2):
for i in range(0, 4):
for j in range(0, 2):
if rh_bbox[i][j] < 0:
rh_bbox[i][j] = 0
elif rh_bbox[i][0] > w:
@ -258,56 +262,51 @@ class mediapipe_detect:
rh_bbox[i][1] = h
else:
pass
cv2.rectangle(image, rh_bbox[0], rh_bbox[3],DrawingSpec.color, DrawingSpec.thickness)
res = {'face_bbox': fl_bbox, 'hand_bbox': [lh_bbox,rh_bbox]}
cv2.rectangle(image, rh_bbox[0], rh_bbox[3], DrawingSpec.color, DrawingSpec.thickness)
res = {'face_bbox': fl_bbox, 'hand_bbox': [lh_bbox, rh_bbox]}
return image, res
def main(input_path, output_path, face_b, left_hand_b, right_hand_b):
cap = cv2.VideoCapture(input_path)
frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = int(cap.get(cv2.CAP_PROP_FPS))
codec = cv2.VideoWriter_fourcc(*'XVID')
video_name = os.path.basename(input_path)
out = cv2.VideoWriter(output_path + "/" + video_name, codec, fps, (frame_width, frame_height))
label = ""
with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:
while True:
ret, frame = cap.read()
if not ret:
break
image, results = mediapipe_detect().mediapipe_detection(frame, holistic)
image, res = mediapipe_detect().get_bbox(image, results, face_b, left_hand_b, right_hand_b, label)
out.write(image)
cv2.namedWindow("mediapipe_detections", cv2.WINDOW_AUTOSIZE)
cv2.imshow("mediapipe_detections", image)
# print(res)
if cv2.waitKey(10) & 0xFF == ord('q'):
break
cap.release()
out.release()
cv2.destroyAllWindows()
# print(res)
return image,res
def main(input_path,output_path,face_b,left_hand_b,right_hand_b):
cap = cv2.VideoCapture(input_path)
frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = int(cap.get(cv2.CAP_PROP_FPS))
codec = cv2.VideoWriter_fourcc(*'XVID')
video_name = os.path.basename(input_path)
out = cv2.VideoWriter(output_path +"/"+ video_name, codec, fps, (frame_width, frame_height))
with mp_holistic.Holistic(min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic:
while True:
ret, frame = cap.read()
if not ret:
break
image, results = mediapipe_detect().mediapipe_detection(frame,holistic)
image,res = mediapipe_detect().get_bbox(image,results,face_b,left_hand_b,right_hand_b)
out.write(image)
cv2.namedWindow("mediapipe_detections", cv2.WINDOW_AUTOSIZE)
cv2.imshow("mediapipe_detections", image)
# print(res)
if cv2.waitKey(10) & 0xFF == ord('q'):
break
cap.release()
out.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
input = 'D:/download/PaddleVideo1/output/output/after_1/test02_0.avi'
# input = 'D:/download/PaddleVideo1/output/output/after_1/test02_0.avi'
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-1_0_1.avi'
# input = 'D:/download/PaddleVideo1/output/output/after_1/0711-3_1400_0.avi'
# input = "C:/Users/Administrator/Pictures/video_seg_re_hand/test01_3.avi"
# input = 'C:/Users/Administrator/Pictures/video3.0/sleep/0711-3_7_01_5.avi'
# input = " D:/download/PaddleVideo1/output/output/after_1/0711-1_199_0.avi"
input = " D:/download/PaddleVideo1/output/output/after_1/0711-1_199_0.avi"
# input = 'D:/download/PaddleVideo1/output/output/after_1/test05_10750_1.avi'
output = 'D:/download/PaddleVideo1/output/output/output'
face_b = 50 #头部标注框修正值
left_hand_b = 7 #左手部分标注框修正值
right_hand_b = 7 #右手部分标注框修正值
main(input,output,face_b,left_hand_b,right_hand_b)
face_b = 50 # 头部标注框修正值
left_hand_b = 7 # 左手部分标注框修正值
right_hand_b = 7 # 右手部分标注框修正值
main(input, output, face_b, left_hand_b, right_hand_b)
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