mirror of
https://github.com/opencv/opencv.git
synced 2025-01-10 14:19:03 +08:00
efbe580ff3
Code Fixes and changed post processing based on models.yml in Object Detection Sample #26486 ## Major Changes 1. Changes to add findModel support for config file in models like yolov4, yolov4-tiny, yolov3, ssd_caffe, tiny-yolo-voc, ssd_tf and faster_rcnn_tf. 2. Added new model and config download links for ssd_caffe, as previous links were not working. 3. Switched to DNN ENGINE_CLASSIC for non-cpu convig as new engine does not support it. 4. Fixes in python sample related to yolov5 usage. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
193 lines
8.8 KiB
Python
193 lines
8.8 KiB
Python
import sys
|
|
import os
|
|
import cv2 as cv
|
|
|
|
|
|
def add_argument(zoo, parser, name, help, required=False, default=None, type=None, action=None, nargs=None, alias=None):
|
|
if alias is not None:
|
|
modelName = alias
|
|
elif len(sys.argv) > 1:
|
|
modelName = sys.argv[1]
|
|
else:
|
|
return
|
|
|
|
if os.path.isfile(zoo):
|
|
fs = cv.FileStorage(zoo, cv.FILE_STORAGE_READ)
|
|
node = fs.getNode(modelName)
|
|
if not node.empty():
|
|
value = node.getNode(name)
|
|
if "sha1" in name:
|
|
prefix = name.replace("sha1", "")
|
|
value = node.getNode(prefix + "load_info")
|
|
if prefix == "config_":
|
|
value = value.getNode("sha1")
|
|
else:
|
|
value = value.getNode(name)
|
|
if "download_sha" in name:
|
|
prefix = name.replace("download_sha", "")
|
|
value = node.getNode(prefix + "load_info")
|
|
value = value.getNode(name)
|
|
if not value.empty():
|
|
if value.isReal():
|
|
default = value.real()
|
|
elif value.isString():
|
|
default = value.string()
|
|
elif value.isInt():
|
|
default = int(value.real())
|
|
elif value.isSeq():
|
|
default = []
|
|
for i in range(value.size()):
|
|
v = value.at(i)
|
|
if v.isInt():
|
|
default.append(int(v.real()))
|
|
elif v.isReal():
|
|
default.append(v.real())
|
|
else:
|
|
print('Unexpected value format')
|
|
exit(0)
|
|
else:
|
|
print('Unexpected field format')
|
|
exit(0)
|
|
required = False
|
|
|
|
if action == 'store_true':
|
|
default = 1 if default == 'true' else (0 if default == 'false' else default)
|
|
assert(default is None or default == 0 or default == 1)
|
|
parser.add_argument('--' + name, required=required, help=help, default=bool(default),
|
|
action=action)
|
|
else:
|
|
parser.add_argument('--' + name, required=required, help=help, default=default,
|
|
action=action, nargs=nargs, type=type)
|
|
|
|
|
|
def add_preproc_args(zoo, parser, sample, alias=None, prefix=""):
|
|
aliases = []
|
|
if os.path.isfile(zoo):
|
|
fs = cv.FileStorage(zoo, cv.FILE_STORAGE_READ)
|
|
root = fs.root()
|
|
for name in root.keys():
|
|
model = root.getNode(name)
|
|
if model.getNode('sample').string() == sample:
|
|
aliases.append(name)
|
|
|
|
parser.add_argument(prefix+'alias', nargs='?', choices=aliases,
|
|
help='An alias name of model to extract preprocessing parameters from models.yml file.')
|
|
add_argument(zoo, parser, prefix+'model',
|
|
help='Path to a binary file of model contains trained weights. '
|
|
'It could be a file with extensions .caffemodel (Caffe), '
|
|
'.pb (TensorFlow), .weights (Darknet), .bin (OpenVINO)', alias=alias)
|
|
add_argument(zoo, parser, prefix+'config',
|
|
help='Path to a text file of model contains network configuration. '
|
|
'It could be a file with extensions .prototxt (Caffe), .pbtxt or .config (TensorFlow), .cfg (Darknet), .xml (OpenVINO)', alias=alias)
|
|
add_argument(zoo, parser, prefix+'mean', nargs='+', type=float, default=[0, 0, 0],
|
|
help='Preprocess input image by subtracting mean values. '
|
|
'Mean values should be in BGR order.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'std', nargs='+', type=float, default=[0, 0, 0],
|
|
help='Preprocess input image by dividing on a standard deviation.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'scale', type=float, default=1.0,
|
|
help='Preprocess input image by multiplying on a scale factor.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'width', type=int,
|
|
help='Preprocess input image by resizing to a specific width.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'height', type=int,
|
|
help='Preprocess input image by resizing to a specific height.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'rgb', action='store_true',
|
|
help='Indicate that model works with RGB input images instead BGR ones.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'labels',
|
|
help='Optional path to a text file with names of labels to label detected objects.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'postprocessing', type=str,
|
|
help='Post-processing kind depends on model topology.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'background_label_id', type=int, default=-1,
|
|
help='An index of background class in predictions. If not negative, exclude such class from list of classes.', alias=alias)
|
|
add_argument(zoo, parser, prefix+'sha1', type=str,
|
|
help='Optional path to hashsum of downloaded model to be loaded from models.yml', alias=alias)
|
|
add_argument(zoo, parser, prefix+'config_sha1', type=str,
|
|
help='Optional path to hashsum of downloaded config to be loaded from models.yml', alias=alias)
|
|
add_argument(zoo, parser, prefix+'download_sha', type=str,
|
|
help='Optional path to hashsum of downloaded model to be loaded from models.yml', alias=alias)
|
|
|
|
def findModel(filename, sha1):
|
|
if filename:
|
|
if os.path.exists(filename):
|
|
return filename
|
|
|
|
fpath = cv.samples.findFile(filename, False)
|
|
if fpath:
|
|
return fpath
|
|
|
|
if os.getenv('OPENCV_DOWNLOAD_CACHE_DIR') is None:
|
|
print('[WARN] Please specify a path to model download directory in OPENCV_DOWNLOAD_CACHE_DIR environment variable.')
|
|
return findFile(filename)
|
|
|
|
if os.path.exists(os.path.join(os.environ['OPENCV_DOWNLOAD_CACHE_DIR'], sha1, filename)):
|
|
return os.path.join(os.environ['OPENCV_DOWNLOAD_CACHE_DIR'], sha1, filename)
|
|
|
|
if os.path.exists(os.path.join(os.environ['OPENCV_DOWNLOAD_CACHE_DIR'], filename)):
|
|
return os.path.join(os.environ['OPENCV_DOWNLOAD_CACHE_DIR'], filename)
|
|
|
|
raise FileNotFoundError('File ' + filename + ' not found! Please specify a path to '
|
|
'model download directory in OPENCV_DOWNLOAD_CACHE_DIR '
|
|
'environment variable or pass a full path to ' + filename)
|
|
|
|
def findFile(filename):
|
|
if filename:
|
|
if os.path.exists(filename):
|
|
return filename
|
|
|
|
fpath = cv.samples.findFile(filename, False)
|
|
if fpath:
|
|
return fpath
|
|
|
|
if os.getenv('OPENCV_SAMPLES_DATA_PATH') is None:
|
|
print('[WARN] Please specify a path to `/samples/data` in OPENCV_SAMPLES_DATA_PATH environment variable.')
|
|
exit(0)
|
|
|
|
if os.path.exists(os.path.join(os.environ['OPENCV_SAMPLES_DATA_PATH'], filename)):
|
|
return os.path.join(os.environ['OPENCV_SAMPLES_DATA_PATH'], filename)
|
|
|
|
for path in ['OPENCV_DNN_TEST_DATA_PATH', 'OPENCV_TEST_DATA_PATH', 'OPENCV_SAMPLES_DATA_PATH']:
|
|
try:
|
|
extraPath = os.environ[path]
|
|
absPath = os.path.join(extraPath, 'dnn', filename)
|
|
if os.path.exists(absPath):
|
|
return absPath
|
|
except KeyError:
|
|
pass
|
|
|
|
raise FileNotFoundError(
|
|
'File ' + filename + ' not found! Please specify the path to '
|
|
'/opencv/samples/data in the OPENCV_SAMPLES_DATA_PATH environment variable, '
|
|
'or specify the path to opencv_extra/testdata in the OPENCV_DNN_TEST_DATA_PATH environment variable, '
|
|
'or specify the path to the model download cache directory in the OPENCV_DOWNLOAD_CACHE_DIR environment variable, '
|
|
'or pass the full path to ' + filename + '.'
|
|
)
|
|
|
|
|
|
def get_backend_id(backend_name):
|
|
backend_ids = {
|
|
"default": cv.dnn.DNN_BACKEND_DEFAULT,
|
|
"openvino": cv.dnn.DNN_BACKEND_INFERENCE_ENGINE,
|
|
"opencv": cv.dnn.DNN_BACKEND_OPENCV,
|
|
"vkcom": cv.dnn.DNN_BACKEND_VKCOM,
|
|
"cuda": cv.dnn.DNN_BACKEND_CUDA
|
|
}
|
|
|
|
if backend_name not in backend_ids:
|
|
raise ValueError(f"Invalid backend name: {backend_name}")
|
|
|
|
return backend_ids[backend_name]
|
|
|
|
def get_target_id(target_name):
|
|
target_ids = {
|
|
"cpu": cv.dnn.DNN_TARGET_CPU,
|
|
"opencl": cv.dnn.DNN_TARGET_OPENCL,
|
|
"opencl_fp16": cv.dnn.DNN_TARGET_OPENCL_FP16,
|
|
"ncs2_vpu": cv.dnn.DNN_TARGET_MYRIAD,
|
|
"hddl_vpu": cv.dnn.DNN_TARGET_HDDL,
|
|
"vulkan": cv.dnn.DNN_TARGET_VULKAN,
|
|
"cuda": cv.dnn.DNN_TARGET_CUDA,
|
|
"cuda_fp16": cv.dnn.DNN_TARGET_CUDA_FP16
|
|
}
|
|
if target_name not in target_ids:
|
|
raise ValueError(f"Invalid target name: {target_name}")
|
|
|
|
return target_ids[target_name] |