# Data transformation layers-----------------------
layer {
name: "train_transform"
type: "DetectNetTransformation"
bottom: "data"
bottom: "label"
top: "transformed_data"
top: "transformed_label"
detectnet_groundtruth_param: {
stride: 8
layer {
name: "val_transform"
type: "DetectNetTransformation"
bottom: "data"
bottom: "label"
top: "transformed_data"
top: "transformed_label"
detectnet_groundtruth_param: {
stride: 8
layer {
name: "pool3/3x3_s2"
type: "Pooling"
bottom: "inception_3b/output"
top: "pool3/3x3_s2"
pooling_param {
pool: MAX
kernel_size: 1
stride: 1
}
}
Traceback (most recent call last): File "/usr/share/digits/digits/scheduler.py", line 507, in run_task task.run(resources) File "/usr/share/digits/digits/task.py", line 184, in run self.before_run() File "/usr/share/digits/digits/model/tasks/caffe_train.py", line 138, in before_run self.save_files_generic() File "/usr/share/digits/digits/model/tasks/caffe_train.py", line 598, in save_files_generic CaffeTrainTask.net_sanity_check(train_val_network, caffe_pb2.TRAIN) File "/usr/share/digits/digits/model/tasks/caffe_train.py", line 1472, in net_sanity_check layer.name, bottom, "TRAIN" if phase == caffe_pb2.TRAIN else "TEST")) CaffeTrainSanityCheckError: Layer 'inception_4a/1x1' references bottom 'pool3/3x3_s2' at the TRAIN stage however this blob is not included at that stage. Please consider using an include directive to limit the scope of this layer.
# Data transformation layers layer {
name: "train_transform"
type: "DetectNetTransformation"
bottom: "data"
bottom: "label"
top: "transformed_data"
top: "transformed_label"
detectnet_groundtruth_param: {
stride: 8
scale_cvg: 0.4
gridbox_type: GRIDBOX_MIN
coverage_type: RECTANGULAR
min_cvg_len: 20
obj_norm: true
image_size_x: 1000
image_size_y: 1000
crop_bboxes: false
object_class: { src: 1 dst: 0} # obj class 1 -> cvg index 0
}
detectnet_augmentation_param: {
crop_prob: 1
shift_x: 32
shift_y: 32
flip_prob: 0.5
rotation_prob: 0
max_rotate_degree: 5
scale_prob: 0.4
scale_min: 0.8
scale_max: 1.2
hue_rotation_prob: 0.8
hue_rotation: 30 desaturation_prob: 0.8 desaturation_max: 0.8
} transform_param: {
mean_value: 127 }
include: { phase: TRAIN } }
layer {
name: "val_transform"
type: "DetectNetTransformation"
bottom: "data"
bottom: "label"
top: "transformed_data"
top: "transformed_label"
detectnet_groundtruth_param: {
stride: 8
scale_cvg: 0.4
gridbox_type: GRIDBOX_MIN
coverage_type: RECTANGULAR
min_cvg_len: 20
obj_norm: true
image_size_x: 1000
image_size_y: 1000
layer {
top: 'bbox-list-class0' python_param {
module: 'caffe.layers.detectnet.clustering'
layer: 'ClusterDetections'
param_str : '1000, 1000, 8, 0.6, 3, 0.02, 22, 1' }
include: { phase: TEST } }
# Calculate mean average precision layer {
type: 'Python'
name: 'cluster_gt'
bottom: 'coverage-label'
bottom: 'bbox-label'
top: 'bbox-list-label-class0' python_param {
module: 'caffe.layers.detectnet.clustering'
layer: 'ClusterGroundtruth'
param_str : '1000, 1000, 8, 1'
}
include: { phase: TEST stage: "val" } }
layer {
type: 'Python'
name: 'score-class0'
bottom: 'bbox-list-label-class0'
bottom: 'bbox-list-class0'
top: 'bbox-list-scored-class0'
python_param {
module: 'caffe.layers.detectnet.mean_ap'
layer: 'ScoreDetections' }
include: { phase: TEST stage: "val" } }
layer {
type: 'Python'
name: 'mAP-class0'
bottom: 'bbox-list-scored-class0'
top: 'mAP-class0'
top: 'precision-class0'
top: 'recall-class0'
python_param {
module: 'caffe.layers.detectnet.mean_ap'
layer: 'mAP'
param_str : '1000, 1000, 8'
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Failed to allocate 133693440 bytes on device 0. Total memory: 12787122176, Free: 107347968, dev_info[0]: total=12787122176 free=107347968