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import random, math | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import matplotlib.patheffects as mpe | |
""" | |
dataset | |
""" |
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import numpy as np | |
import matplotlib.pyplot as plt | |
def get_bboxes_from(output): | |
""" returns list of bboxes """ | |
return outputs["instances"].__dict__['_fields']['pred_boxes'].__dict__['tensor'] | |
def crop(bbox, in_img: np.ndarray): | |
""" bbox is a list with xmin, ymin, xmax, ymax """ |
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@startuml | |
!define LIGHTSTYLE | |
!includeurl https://gist.githubusercontent.com/rakesh4real/39df62ab1d17d252e20d42e9ef389c42/raw/ab750998a1ebd9ead7fbd4e5e20ad93c55bbb028/plantuml_style.puml | |
class Object << general >> | |
Object <|--- ArrayList : parent | |
note top of Object : In java, every class\nextends this one. |
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def train(): | |
tf.global_variables_initializer().run() | |
could_load, checkpoint_counter = load() | |
if could_load: | |
start_epoch = (int)(checkpoint_counter / num_batches) | |
start_batch_id = checkpoint_counter - start_epoch * num_batches | |
counter = checkpoint_counter | |
print("[INFO] Checkpoint Load Success!") |
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# importing the multiprocessing module | |
import multiprocessing | |
def print_cube(num): | |
""" | |
function to print cube of given num | |
""" | |
while True: | |
print("Cube: {}".format(num * num * num)) | |
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