config.yaml

defaults:
  - _self_
  - metadataScaling
  - enhancer
  - yolos
  - estrnn
  
seed: 42
numGroups: 8
growthRate: 32
currentDir: ${hydra:runtime.cwd}

# MARK: - transformer
model: null
dummy: False
hiddenDims: 512
numHead: 8
numEncoderLayer: 6
numDecoderLayer: 6
dimFeedForward: 2048
dropout: .1
numQuery: 80
numClass: 4
numBlocks:
  - 6
  - 6
  - 6
  - 6
inChans: 1

# MARK: - yolo dataset
targetHeight: 608
targetWidth: 608

# MARK: - miscellaneous
device: cuda
weight: ""


# MARK: - training config
lr: 5e-7
lrBackbone: 1e-5
batchSize: 8
weightDecay: 1e-4
epochs: 100
lrDrop: 1000
clipMaxNorm: .1
patience: 15

# MARK: - loss
classCost: .005
bboxCost: 5.
giouCost: 2.5
eosCost: .1

# MARK: - dataset
cropBackground: False
dataDir: ${hydra:runtime.cwd}/data/
trainAnnFile: ${hydra:runtime.cwd}/data/new/Train.json
valAnnFile: ${hydra:runtime.cwd}/data/new/Valid.json
testAnnFile: ${hydra:runtime.cwd}/data/new/Test.json

# MARK: - video dataset
trainVideoFrames: ${hydra:runtime.cwd}/data/new/videoFrames/Train
valVideoFrames: ${hydra:runtime.cwd}/data/new/videoFrames/Valid
testVideoFrames: ${hydra:runtime.cwd}/data/new/videoFrames/Test
videoDir: ${hydra:runtime.cwd}/data/Video Clips
numFrames: 4

spynet:
  weights: ${hydra:runtime.cwd}/checkpoint/spynet/network-sintel-final.pytorch
  freeze: True

# MARK: - miscellaneous
outputDir: ${hydra:runtime.cwd}/checkpoint
taskName: DETR
numWorkers: 1
multi: False
amp: False

# MARK: - wandb
wandbEntity: marcoparola
wandbProject: conditioning-transformer

inference:
  savePlot: False
  showPlot: False
  savePrediction: False