'''
predict.py有几个注意点
1、无法进行批量预测，如果想要批量预测，可以利用os.listdir()遍历文件夹，利用Image.open打开图片文件进行预测。
2、如果想要保存，利用r_image.save("img.jpg")即可保存。
3、如果想要获得框的坐标，可以进入detect_image函数，读取top,left,bottom,right这四个值。
4、如果想要截取下目标，可以利用获取到的top,left,bottom,right这四个值在原图上利用矩阵的方式进行截取。
'''
from frcnn import FRCNN
from PIL import Image
frcnn = FRCNN()
while True:
img = input('Input image filename:')
try:
image = Image.open(img)
#-------------------------------------#
# 转换成RGB图片，可以用于灰度图预测。
#-------------------------------------#
image = image.convert("RGB")
except:
print('Open Error! Try again!')
continue
else:
r_image = frcnn.detect_image(image)
r_image.show()
frcnn = FRCNN()
# 调用摄像头
capture = cv2.VideoCapture(0) # capture=cv2.VideoCapture("1.mp4")
fps = 0.0
while (True):
t1 = time.time()
# 读取某一帧
ref, frame = capture.read()
# 格式转变，BGRtoRGB
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# 转变成Image
frame = Image.fromarray(np.uint8(frame))
# 进行检测
frame = np.array(frcnn.detect_image(frame))
# RGBtoBGR满足opencv显示格式
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
fps = (fps + (1. / (time.time() - t1))) / 2
print("fps= %.2f" % (fps))
frame = cv2.putText(frame, "fps= %.2f" % (fps), (0, 40),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.imshow("video", frame)
c = cv2.waitKey(30) & 0xff
if c == 27:
capture.release()
break
# img = 'dataset/test/images/006486001008661.jpg'
# image = Image.open(img)
# r_image = frcnn.detect_image(image)
# r_image.save('result.jpg')
testdata_file = 'dataset/main/test.txt'
f = open(testdata_file)
lines = f.readlines()
result = open('result.txt', 'w')
for l in lines:
l = l.strip()
img = "dataset/test/images/%s.jpg" % l
image = Image.open(img)
bbox, conf, label = frcnn.detect_image(image)
if len(bbox) == 0:
continue
for i in range(len(bbox)):
score = conf[i] # 置信度
left, top, right, bottom = bbox[i] # 框框位置
result.write(l)
result.write(' ' + str(score))
result.write(' ' + str(left))
result.write(' ' + str(top))
result.write(' ' + str(right))
result.write(' ' + str(bottom) + '\n')
result.close()
63.25, 65.25, 73.25, 60.25, 62.25, 62.25, 62.25, 62.25, 53.25, 70.25,
70.25, 71.25, 60.25, 69.25, 54.25, 74.25, 67.25, 76.25, 58.25, 63.25,
61.25, 69.25, 64.25, 70.25, 57.25, 76.25, 66.25, 66.25, 76.25, 59.25,
83.25, 63.25, 56.25, 73.25, 65.25, 43.25, 56.25, 52.25, 57.25, 80.25,
59.25, 56.25, 46.25, 53.25, 54.25, 55.25, 50.25, 58.25, 52.25, 63.25,
71.25, 52.25, 56.25, 47.25, 49.25, 60.25, 71.25, 54.25, 51.25, 63.25,
53.25, 51.25, 39.25, 45.25, 49.25, 51.25, 38.25, 51.25, 50.25, 63.25,
35.25, 44.25, 60.25, 91.25, 47.25, 43.25, 49.25, 54.25, 33.25, 48.25,
61.25, 52.25, 49.25, 38.25, 56.25, 40.25, 41.25, 25.25, 43.25, 39.25,
34.25, 59.25, 57.25, 32.25, 48.25, 40.25, 52.25, 22.25, 39.25, 47.25,
53.25, 38.25, 36.25, 32.25, 58.25, 45.25, 49.25, 45.25, 47.25, 33.25,
65.25, 31.25, 45.25, 25.25, 36.25, 47.25, 21.25, 53.25, 41.25, 37.25,
51.25, 58.25, 43.25, 36.25, 44.25, 27.25, 46.25, 45.25, 29.25, 41.25,
41.25, 57.25, 44.25, 49.25, 34.25, 47.25, 38.25, 69.25, 32.25, 51.25,
45.25, 21.25, 36.25, 41.25, 51.25, 55.25, 30.25, 45.25, 30.25, 27.25,
42.25, 46.25, 54.25, 32.25, 29.25, 32.25, 46.25, 41.25, 13.25, 18.25,
42.25, 25.25, 47.25, 33.25, 47.25, 33.25, 20.25, 38.25, 30.25, 34.25,
41.25, 32.25, 26.25, 48.25, 44.25, 39.25, 56.25, 58.25, 32.25, 25.25,
32.25, 43.25, 40.25, 31.25, 35.25, 44.25, 42.25, 39.25, 43.25, 43.25,
97.25, 29.25, 29.25, 54.25, 27.25, 32.25, 39.25, 24.25, 41.25, 21.25,
16.25, 28.25, 52.25, 38.25, 26.25, 28.25, 31.25, 34.25, 42.25, 57.25,
25.25, 9.25, 42.25, 40.25, 30.25, 30.25, 49.25, 37.25, 51.25, 39.25, 54.25,
35.25, 58.25, 33.25, 46.25, 41.25, 47.25, 34.25, 36.25, 42.25, 41.25,
23.25, 66.25, 25.25, 34.25, 32.25, 37.25, 18.25, 37.25, 35.25, 56.25,
45.25, 47.25, 38.25, 47.25, 43.25, 40.25, 47.25, 58.25, 32.25, 40.25,
10.25, 7.25, 8.25, -5.75, 47.25, 44.25, 42.25, 49.25, 51.25, 57.25, 39.25,
26.25, 26.25, 29.25, 39.25, 39.25, -19.75, 0.25, 4.25, -4.75
]
alter_raman = frcnn.detect_image(raman)
frcnn.close_session()
2、如果想要进行检测完的图片的保存，利用r_image.save("img.jpg")即可保存，直接在predict.py里进行修改即可。
3、如果想要获得预测框的坐标，可以进入frcnn.detect_image函数，在绘图部分读取top，left，bottom，right这四个值。
4、如果想要利用预测框截取下目标，可以进入frcnn.detect_image函数，在绘图部分利用获取到的top，left，bottom，right这四个值
在原图上利用矩阵的方式进行截取。
5、如果想要在预测图上写额外的字，比如检测到的特定目标的数量，可以进入frcnn.detect_image函数，在绘图部分对predicted_class进行判断，
比如判断if predicted_class == 'car': 即可判断当前目标是否为车，然后记录数量即可。利用draw.text即可写字。
'''
while True:
img = input('Input image filename:')
try:
image = Image.open(img)
except:
print('Open Error! Try again!')
continue
else:
r_image = frcnn.detect_image(image, crop=crop)
r_image.show()
elif mode == "video":
capture = cv2.VideoCapture(video_path)
if video_save_path != "":
fourcc = cv2.VideoWriter_fourcc(*'XVID')
size = (int(capture.get(cv2.CAP_PROP_FRAME_WIDTH)),
int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT)))
out = cv2.VideoWriter(video_save_path, fourcc, video_fps, size)
fps = 0.0
while (True):
t1 = time.time()
# 读取某一帧
ref, frame = capture.read()
help='num img 2 show',
default=1)
parser.add_argument('-r',
"--root",
type=str,
help='root dir filled with *.jpg')
parser.add_argument('-i', "--filename", type=str, help='filename', default='')
args = parser.parse_args()
frcnn = FRCNN(args.model_path, args.backbone, args.conf)
# efficientdet = EfficientDet(args.model_path, args.version, args.conf, args.cuda)
if args.num2show == 1:
image = Image.open(os.path.join(args.root, args.filename))
res, cls, score = frcnn.detect_image(image)
print(cls, score)
else:
print('结果将会保存到temp.png')
files = os.listdir(args.root)
idx = [
int(len(os.listdir(args.root)) * random.random())
for i in range(args.num2show)
]
imgs = [Image.open(os.path.join(args.root, files[id])) for id in idx]
ress, clss, scores = [], [], []
print(len(imgs))
for img in imgs:
res, cls, score = frcnn.detect_image(img)
ress.append(res)
2、如果想要进行检测完的图片的保存，利用r_image.save("img.jpg")即可保存，直接在predict.py里进行修改即可。
3、如果想要获得预测框的坐标，可以进入frcnn.detect_image函数，在绘图部分读取top，left，bottom，right这四个值。
4、如果想要利用预测框截取下目标，可以进入frcnn.detect_image函数，在绘图部分利用获取到的top，left，bottom，right这四个值
在原图上利用矩阵的方式进行截取。
5、如果想要在预测图上写额外的字，比如检测到的特定目标的数量，可以进入frcnn.detect_image函数，在绘图部分对predicted_class进行判断，
比如判断if predicted_class == 'car': 即可判断当前目标是否为车，然后记录数量即可。利用draw.text即可写字。
'''
while True:
img = input('Input image filename:')
try:
image = Image.open(img)
except:
print('Open Error! Try again!')
continue
else:
r_image = frcnn.detect_image(image)
r_image.show()
elif mode == "video":
capture = cv2.VideoCapture(video_path)
if video_save_path != "":
fourcc = cv2.VideoWriter_fourcc(*'XVID')
size = (int(capture.get(cv2.CAP_PROP_FRAME_WIDTH)),
int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT)))
out = cv2.VideoWriter(video_save_path, fourcc, video_fps, size)
fps = 0.0
while (True):
t1 = time.time()
# 读取某一帧
ref, frame = capture.read()
