Comments (5)
@LymanLiuChina
st like this 😄
import os
# ==============
# === COMMON ===
# ==============
ROOT_FD = "."
# ==========================
# === SEGMENTATION MODEL ===
# ==========================
# Make it True if you want to use the provided coco weights
IS_COCO = False
# keras model directory path
MODEL_FD = os.path.join(ROOT_FD, "models")
# keras model file path
H5_WEIGHT_PATH = os.path.join(
MODEL_FD,
""
)
# Path where the Frozen PB will be save
PATH_TO_SAVE_FROZEN_PB = os.path.join(
MODEL_FD,
"frozen_model"
)
# Name for the Frozen PB name
FROZEN_NAME = 'mask_frozen_graph.pb'
# PATH where to save serving model
PATH_TO_SAVE_TENSORFLOW_SERVING_MODEL = \
os.path.join(ROOT_FD, "serving_model")
# Version of the serving model
VERSION_NUMBER = 1
OD_VERSION_NUMBER = 1
# Number of classes that you have trained your model
NUMBER_OF_CLASSES = 1
# Host-port gRPC
HOST = "http://..."
gRPC_PORT = 8500
REST_PORT = 8501
GRPC_TIMEOUT = 5
MODEL_SIG_NAME = ""
MODEL_SPEC_NAME = ""
REST_MODE = "predict"
# REST-API meta-data
REST_URL_FMT = "{}:{}/v1/models/{}:{}"
REST_URL = REST_URL_FMT.format(
HOST,
REST_PORT,
MODEL_SPEC_NAME,
REST_MODE
)
# Input meta-data
IMAGE_SIZE = 640
IN_TENSOR_IMAGE = "input_image"
IN_TENSOR_IMAGE_META = "input_image_meta"
IN_TENSOR_ANCHORS = "input_anchors"
IN_TENSOR_DTYPE = "float32"
# Output meta-data
OUT_TENSOR_DETECTION = "mrcnn_detection/Reshape_1"
OUT_TENSOR_MASK = "mrcnn_mask/Reshape_1"
OUT_DETECTION_SHAPE = (6,)
OUT_MASK_SHAPE = (28, 28, NUMBER_OF_CLASSES + 1)
# Class meta-data
CLASSES = []
from matterport-maskrcnn-with-tensorflow-serving.
what is this from api.helpers import utils as api_utils ?please,could you give your complete program code?
from matterport-maskrcnn-with-tensorflow-serving.
thanks,I got it!
from matterport-maskrcnn-with-tensorflow-serving.
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from matterport-maskrcnn-with-tensorflow-serving.
@LymanLiuChina
Did you read README.md? 😃
I just took some functions in mrcnn/model.py, for example: api_utils.get_anchors & api_utils.unmold_detections
from matterport-maskrcnn-with-tensorflow-serving.
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