blob: df0892d5f7f035ffae19826d84df81a0f0f2645d [file] [log] [blame]
# Copyright 2019 Google LLC
#
# 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
#
# https://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 collections
import os
import re
import time
LABEL_PATTERN = re.compile(r'\s*(\d+)(.+)')
def load_labels(path):
with open(path, 'r', encoding='utf-8') as f:
lines = (LABEL_PATTERN.match(line).groups() for line in f.readlines())
return {int(num): text.strip() for num, text in lines}
def input_image_size(engine):
_, h, w, _ = engine.get_input_tensor_shape()
return w, h
def same_input_image_sizes(engines):
return len({input_image_size(engine) for engine in engines}) == 1
def avg_fps_counter(window_size):
window = collections.deque(maxlen=window_size)
prev = time.monotonic()
yield 0.0 # First fps value.
while True:
curr = time.monotonic()
window.append(curr - prev)
prev = curr
yield len(window) / sum(window)
def make_engines(models, engine_class):
engines, titles = [], {}
for model in models.split(','):
if '@' in model:
model_path, title = model.split('@')
else:
model_path, title = model, os.path.basename(os.path.normpath(model))
engine = engine_class(model_path)
engines.append(engine)
titles[engine] = title
return engines, titles