PaddleClas/deploy/python/predict_system.py

66 lines
2.1 KiB
Python

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
__dir__ = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.abspath(os.path.join(__dir__, '../')))
import copy
import cv2
import numpy as np
from python.predict_rec import RecPredictor
from python.predict_det import DetPredictor
from utils import logger
from utils import config
from utils.get_image_list import get_image_list
class SystemPredictor(object):
def __init__(self, config):
self.rec_predictor = RecPredictor(config)
self.det_predictor = DetPredictor(config)
def predict(self, img):
output = []
results = self.det_predictor.predict(img)
for result in results:
print(result)
xmin, xmax, ymin, ymax = result["bbox"].astype("int")
crop_img = img[xmin:xmax, ymin:ymax, :].copy()
rec_results = self.rec_predictor.predict(crop_img)
result["featrue"] = rec_results
output.append(result)
return output
def main(config):
system_predictor = SystemPredictor(config)
image_list = get_image_list(config["Global"]["infer_imgs"])
assert config["Global"]["batch_size"] == 1
for idx, image_file in enumerate(image_list):
img = cv2.imread(image_file)[:, :, ::-1]
output = system_predictor.predict(img)
print(output)
return
if __name__ == "__main__":
args = config.parse_args()
config = config.get_config(args.config, overrides=args.override, show=True)
main(config)