import cv2
import pathlib
from objdetect import ObjDetectApi
PATH_TO_LABELS = 'data/mscoco_label_map.pbtxt'
MODEL_NAME = 'ssd_mobilenet_v1_coco_2017_11_17'
api = ObjDetectApi(MODEL_NAME, PATH_TO_LABELS)
# 예제 데이터
PATH_TO_TEST_IMAGES_DIR = pathlib.Path('test_images')
TEST_IMAGE_PATHS = sorted(list(PATH_TO_TEST_IMAGES_DIR.glob("*.jpg")))
# 검출 진행
for image_path in TEST_IMAGE_PATHS:
image, output_dict = api.inference_file(image_path)
print(output_dict)
labeled_image = api.visualize(image, output_dict)
labeled_image = cv2.cvtColor(labeled_image, cv2.COLOR_RGB2BGR)
cv2.imshow('image', labeled_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
import cv2
import net
import json
import numpy as np
from objdetect import ObjDetectApi, NumpyEncoder
PATH_TO_LABELS = 'data/mscoco_label_map.pbtxt'
MODEL_NAME = 'ssd_mobilenet_v1_coco_2017_11_17'
api = ObjDetectApi(MODEL_NAME, PATH_TO_LABELS)
HOST = '0.0.0.0'
PORT = 5000
def filtering(output_dict):
classes = []
boxes = []
scores = []
for ix, score in enumerate(output_dict['detection_scores']):
if score > 0.5:
print(score)
classes.append(output_dict['detection_classes'][ix])
boxes.append(output_dict['detection_boxes'][ix])
scores.append(score)
return {
'detection_classes': np.array(classes),
'detection_boxes': np.array(boxes),
'detection_scores': np.array(scores)
}
from video import Video
import socket
import json
import net
import cv2
import numpy as np
from objdetect import ObjDetectApi, NumpyDecoder
PATH_TO_LABELS = 'data/mscoco_label_map.pbtxt'
MODEL_NAME = 'ssd_mobilenet_v1_coco_2017_11_17'
api = ObjDetectApi(MODEL_NAME, PATH_TO_LABELS)
HOST = '127.0.0.1'
PORT = 5000
if __name__ == '__main__':
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
s.connect((HOST, PORT))
writer = s.makefile('wb')
reader = s.makefile('rb')
with Video(device=0) as v:
for image in v:
jpg = Video.to_jpg(image)
net.send(writer, jpg)
output_dict = net.receive(reader)[0].decode()
output_dict = json.loads(output_dict, cls=NumpyDecoder)
labeled_image = api.visualize(image, output_dict)
cv2.imshow('frame', labeled_image)
key = cv2.waitKey(1)
