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AI: Update log messages and tests in internal/ai/classify #127 #5011

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Signed-off-by: Michael Mayer <michael@photoprism.app>
This commit is contained in:
Michael Mayer
2025-08-04 10:31:39 +02:00
parent 523605f7d7
commit 3177a61f75
3 changed files with 38 additions and 37 deletions
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42
internal/ai/classify/model_test.go
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@@ -37,7 +37,7 @@ func TestModel_CenterCrop(t *testing.T) {
model.meta.Input.ResizeOperation = tensorflow.CenterCrop
t.Run("nasnet padding", func(t *testing.T) {
testModel_BasicLabels(t, model, 6)
runBasicLabelsTest(t, model, 6)
})
}
@@ -50,7 +50,7 @@ func TestModel_Padding(t *testing.T) {
model.meta.Input.ResizeOperation = tensorflow.Padding
t.Run("nasnet padding", func(t *testing.T) {
testModel_BasicLabels(t, model, 6)
runBasicLabelsTest(t, model, 6)
})
}
@@ -63,11 +63,11 @@ func TestModel_ResizeBreakAspectRatio(t *testing.T) {
model.meta.Input.ResizeOperation = tensorflow.ResizeBreakAspectRatio
t.Run("nasnet break aspect ratio", func(t *testing.T) {
testModel_BasicLabels(t, model, 4)
runBasicLabelsTest(t, model, 4)
})
}
func testModel_BasicLabels(t *testing.T, model *Model, expectedUncertainty int) {
func runBasicLabelsTest(t *testing.T, model *Model, expectedUncertainty int) {
result, err := model.File(examplesPath+"/zebra_green_brown.jpg", 10)
assert.NoError(t, err)
@@ -146,14 +146,14 @@ func TestModel_LabelsFromFile(t *testing.T) {
assert.Equal(t, 70, result[0].Uncertainty)
}
})
t.Run("not existing file", func(t *testing.T) {
t.Run("NotExistingFile", func(t *testing.T) {
tensorFlow := NewModelTest(t)
result, err := tensorFlow.File(examplesPath+"/notexisting.jpg", 10)
assert.Contains(t, err.Error(), "no such file or directory")
assert.Empty(t, result)
})
t.Run("disabled true", func(t *testing.T) {
t.Run("Disabled", func(t *testing.T) {
tensorFlow := NewNasnet(assetsPath, true)
result, err := tensorFlow.File(examplesPath+"/chameleon_lime.jpg", 10)
@@ -252,7 +252,7 @@ func TestModel_Run(t *testing.T) {
assert.Empty(t, result)
}
})
t.Run("disabled true", func(t *testing.T) {
t.Run("Disabled", func(t *testing.T) {
tensorFlow := NewNasnet(assetsPath, true)
if imageBuffer, err := os.ReadFile(examplesPath + "/dog_orange.jpg"); err != nil {
@@ -272,16 +272,16 @@ func TestModel_Run(t *testing.T) {
}
func TestModel_LoadModel(t *testing.T) {
t.Run("model loaded", func(t *testing.T) {
t.Run("Success", func(t *testing.T) {
tf := NewModelTest(t)
assert.True(t, tf.ModelLoaded())
})
t.Run("model path does not exist", func(t *testing.T) {
t.Run("NotFound", func(t *testing.T) {
tensorFlow := NewNasnet(assetsPath+"foo", false)
err := tensorFlow.loadModel()
if err != nil {
assert.Contains(t, err.Error(), "could not find SavedModel")
assert.Contains(t, err.Error(), "not find SavedModel")
}
assert.Error(t, err)
@@ -289,17 +289,7 @@ func TestModel_LoadModel(t *testing.T) {
}
func TestModel_BestLabels(t *testing.T) {
t.Run("labels not loaded", func(t *testing.T) {
tensorFlow := NewNasnet(assetsPath, false)
p := make([]float32, 1000)
p[666] = 0.5
result := tensorFlow.bestLabels(p, 10)
assert.Empty(t, result)
})
t.Run("labels loaded", func(t *testing.T) {
t.Run("Success", func(t *testing.T) {
tensorFlow := NewNasnet(assetsPath, false)
if err := tensorFlow.loadLabels(modelPath); err != nil {
@@ -317,4 +307,14 @@ func TestModel_BestLabels(t *testing.T) {
assert.Equal(t, "image", result[0].Source)
t.Log(result)
})
t.Run("NotLoaded", func(t *testing.T) {
tensorFlow := NewNasnet(assetsPath, false)
p := make([]float32, 1000)
p[666] = 0.5
result := tensorFlow.bestLabels(p, 10)
assert.Empty(t, result)
})
}