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config.ini
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config.ini
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[config]
; yolo yolo2
model = yolo2
basedir = ~/Documents/Database/yolo-tf
[queue]
capacity = 320
min_after_dequeue=160
[cache]
names = config/names/80
datasets = config/cache/coco.tsv:config/cache/voc.tsv
[data_augmentation_full]
enable = 1
enable_probability = 0.5
random_crop = 0.9
[data_augmentation_resized]
enable = 1
enable_probability = 0.5
random_flip_horizontally = 1
random_brightness = 1
random_contrast = 1
random_saturation = 1
random_hue = 1
noise = 1
grayscale_probability = 0.05
[exponential_decay]
decay_steps = 100000
decay_rate = 0.96
staircase = 1
[optimizer_adam]
beta1 = 0.9
beta2 = 0.999
epsilon = 1e-8
[optimizer_adadelta]
rho = 0.95
epsilon = 1e-8
[optimizer_adagrad]
initial_accumulator_value = 0.1
[optimizer_momentum]
momentum = 0.9
[optimizer_rmsprop]
decay = 0.9
momentum = 0
epsilon = 1e-10
[optimizer_ftrl]
learning_rate_power = -0.5
initial_accumulator_value = 0.1
l1_regularization_strength = 0
l2_regularization_strength = 0
[summary]
; (total_loss\/objectives\/(iou_best|iou_normal|coords|prob)|total_loss)$
scalar = (total_loss\/objectives\/(iou_best|iou_normal|coords|prob)|total_loss)$
scalar_reduce = tf.reduce_mean
; [_\w\d]+\/(input|conv\d*\/(convolution|leaky_relu\/data))$
; [_\w\d]+\/(passthrough|reorg)$
image_ = [_\w\d]+\/(input|conv\d*\/(convolution|leaky_relu\/data))$
image_max = 1
; [_\w\d]+\/(conv|fc)\d*\/(weights|biases)$
; [_\w\d]+\/(conv|fc)\d*\/BatchNorm\/(gamma|beta)$
; [_\w\d]+\/(conv|fc)\d*\/BatchNorm\/moments\/normalize\/(mean|variance)$
; [_\w\d]+\/(conv|fc)\d*\/BatchNorm\/(moving_mean|moving_variance)$
; [_\w\d]+\/(conv|fc)\d*\/(convolution|leaky_relu\/data)$
; [_\w\d]+\/(input|conv0\/convolution)$
histogram_ = [_\w\d]+\/(input|conv0\/convolution)$
gradients = 0
[yolo]
inference = tiny
width = 448
height = 448
boxes_per_cell = 2
[yolo_hparam]
prob = 1
iou_best = 1
iou_normal = .5
coords = 5
[yolo2]
inference = darknet
width = 416
height = 416
anchors = config/yolo2/anchors/coco.tsv
[yolo2_hparam]
prob = 1
iou_best = 5
iou_normal = 1
coords = 1