quietlight/Skraak - Change 4BTZNCRM7R6SZPE5W7UENKS2LNXXRWVXGGZAM7QOWDIPEGW3LQ6AC

catch up commit before starting work

Created by quietlight on March 1, 2024

4BTZNCRM7R6SZPE5W7UENKS2LNXXRWVXGGZAM7QOWDIPEGW3LQ6AC

Dependencies

In channels

main

Change contents

Replacement in src/Train.jl at line 28 [3.335620]

B:BD[2.122] → [2.122:174]

train("K1-7_R50", 20, glob_pattern, true, 0.90, 32)

[2.122]

[4.0]

train("K1-8_Colour", 20, glob_pattern, true, 0.90, 64)

Replacement in src/Train.jl at line 233 [3.335620]

B:BD[3.342176] → [2.629:773]

    fst = Metalhead.ResNet(50, pretrain = pretrain).layers
    lst = Flux.Chain(AdaptiveMeanPool((1, 1)), Flux.flatten, Dense(2048 => classes))

[3.342176]

[3.342319]

    fst = Metalhead.ResNet(18, pretrain = pretrain).layers
    lst = Flux.Chain(AdaptiveMeanPool((1, 1)), Flux.flatten, Dense(512 => classes))

Replacement in src/Train.jl at line 245 [3.335620]

B:BD[3.342795] → [2.774:917]

    f = Metalhead.ResNet(50, pretrain = false).layers
    l = Flux.Chain(AdaptiveMeanPool((1, 1)), Flux.flatten, Dense(2048 => model_classes))

[3.342795]

[3.342937]

    f = Metalhead.ResNet(18, pretrain = false).layers
    l = Flux.Chain(AdaptiveMeanPool((1, 1)), Flux.flatten, Dense(512 => model_classes))

Replacement in src/Train.jl at line 253 [3.335620]

B:BD[3.343093] → [2.918:1007]

        lst = Flux.Chain(AdaptiveMeanPool((1, 1)), Flux.flatten, Dense(2048 => classes))

[3.343093]

[3.343181]

        lst = Flux.Chain(AdaptiveMeanPool((1, 1)), Flux.flatten, Dense(512 => classes))

Replacement in src/Predict.jl at line 33 [3.366496]

B:BD[5.22] → [2.1065:1249]

model = "/media/david/SSD2/PrimaryDataset/model_K1-7_CPU_epoch-17-0.9126-2024-02-04.jld2"
model = "/media/david/SSD2/PrimaryDataset/model_K1-7_R50_CPU_epoch-20-0.9136-2024-02-07.jld2"

[5.22]

[3.367291]

model = "/media/david/SSD2/PrimaryDataset/model_K1-8_Colour_CPU_epoch-14-0.9129-2024-02-16.jld2"

Replacement in src/Predict.jl at line 61 [3.366496]

B:BD[6.462] → [2.1388:1531]

    f = Metalhead.ResNet(50, pretrain = false).layers
    l = Flux.Chain(AdaptiveMeanPool((1, 1)), Flux.flatten, Dense(2048 => model_classes))

[6.462]

[6.604]

    f = Metalhead.ResNet(18, pretrain = false).layers
    l = Flux.Chain(AdaptiveMeanPool((1, 1)), Flux.flatten, Dense(512 => model_classes))

Insertion in src/Predict.jl at line 208 [3.366496]
[3.373189]
[2.1633]
```
#= not needed
```

Replacement in src/Predict.jl at line 213 [3.366496]

B:BD[2.1756] → [2.1756:1807]

        x -> collect(channelview(float32.(x))) |>

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[2.1807]

        # x -> collect(channelview(float32.(x))) |>

Insertion in src/Predict.jl at line 218 [3.366496]
[2.1889]
[2.1889]
```
=#
```

Replacement in src/Predict.jl at line 232 [3.366496]

B:BD[6.4269] → [6.4269:4349]

    raw_images = ThreadsX.map(x -> get_image_for_inference(x, f), split_signal)

[6.4269]

[6.4349]

    raw_images = ThreadsX.map(x -> get_image_from_sample(x, f), split_signal)

Replacement in src/Clips.jl at line 209 [7.12356]

∅:D[2.2054] → [7.19231:19291]

B:BD[7.19231] → [7.19231:19291]

        x -> RGB.(x) |> 
        x -> imresize(x, 224, 224)

[2.2054]

[7.19291]

        #x -> RGB.(x) |> 
        x -> imresize(x, 224, 224) |>
        x -> Float32.(x)