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Added labels download to model_external_test

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If a model needs to have its labels downloaded from another source, it
can now be added to the test information.
This commit is contained in:
raystlin
2025-07-26 22:27:20 +00:00
parent eef76ded5f
commit aeba5bfc4c
1 changed files with 77 additions and 36 deletions
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113
internal/ai/classify/model_external_test.go
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@@ -27,56 +27,77 @@ var baseUrl = "https://dl.photoprism.app/tensorflow/vision"
//To avoid downloading everything again and again...
//var baseUrl = "http://host.docker.internal:8000"
var modelsInfo = map[string]*tensorflow.ModelInfo{
type ModelTestCase struct {
Info *tensorflow.ModelInfo
Labels string
}
var modelsInfo = map[string]*ModelTestCase{
"efficientnet-v2-tensorflow2-imagenet1k-b0-classification-v2.tar.gz": {
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
Info: &tensorflow.ModelInfo{
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
},
},
},
"efficientnet-v2-tensorflow2-imagenet1k-m-classification-v2.tar.gz": {
Input: &tensorflow.PhotoInput{
Height: 480,
Width: 480,
},
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
Info: &tensorflow.ModelInfo{
Input: &tensorflow.PhotoInput{
Height: 480,
Width: 480,
},
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
},
},
},
"efficientnet-v2-tensorflow2-imagenet21k-b0-classification-v1.tar.gz": {
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
Info: &tensorflow.ModelInfo{
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
},
},
Labels: "labels-imagenet21k.txt",
},
"inception-v3-tensorflow2-classification-v2.tar.gz": {
Input: &tensorflow.PhotoInput{
Height: 299,
Width: 299,
},
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
Info: &tensorflow.ModelInfo{
Input: &tensorflow.PhotoInput{
Height: 299,
Width: 299,
},
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
},
},
},
"resnet-v2-tensorflow2-101-classification-v2.tar.gz": {
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
Info: &tensorflow.ModelInfo{
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
},
},
},
"resnet-v2-tensorflow2-152-classification-v2.tar.gz": {
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
Info: &tensorflow.ModelInfo{
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
},
},
},
"vision-transformer-tensorflow2-vit-b16-classification-v1.tar.gz": {
Input: &tensorflow.PhotoInput{
Intervals: []tensorflow.Interval{
{
Start: -1.0,
End: 1.0,
Info: &tensorflow.ModelInfo{
Input: &tensorflow.PhotoInput{
Intervals: []tensorflow.Interval{
{
Start: -1.0,
End: 1.0,
},
},
},
},
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
Output: &tensorflow.ModelOutput{
OutputsLogits: true,
},
},
},
}
@@ -113,7 +134,14 @@ func TestExternalModel_AllModels(t *testing.T) {
downloadedModel := downloadRemoteModel(t, fmt.Sprintf("%s/%s", baseUrl, k), tmpPath)
log.Infof("Model downloaded to %s", downloadedModel)
model := NewModel(tmpPath, downloadedModel, modelPath, v, false)
if v.Labels != "" {
modelPath := filepath.Join(tmpPath, downloadedModel)
t.Logf("Model path: %s", modelPath)
downloadLabels(t, fmt.Sprintf("%s/%s", baseUrl, v.Labels), modelPath)
}
model := NewModel(tmpPath, downloadedModel, modelPath, v.Info, false)
if err := model.loadModel(); err != nil {
t.Fatal(err)
}
@@ -128,6 +156,25 @@ func TestExternalModel_AllModels(t *testing.T) {
}
}
func downloadLabels(t *testing.T, url, dst string) {
resp, err := http.Get(url)
if err != nil {
t.Fatal(err)
}
defer resp.Body.Close()
output, err := os.Create(filepath.Join(dst, "labels.txt"))
if err != nil {
t.Fatal(err)
}
defer output.Close()
_, err = io.Copy(output, resp.Body)
if err != nil {
t.Fatal(err)
}
}
func downloadRemoteModel(t *testing.T, url, tmpPath string) (model string) {
t.Logf("Downloading %s to %s", url, tmpPath)
@@ -248,7 +295,6 @@ func testModel_LabelsFromFile(t *testing.T, tensorFlow *Model) {
if len(result) > 0 {
assertContainsAny(t, result[0].Name, []string{"cat", "kitty"})
//assert.Equal(t, 59, result[0].Uncertainty)
}
})
t.Run(testName("cat_720.jpeg"), func(t *testing.T) {
@@ -268,7 +314,6 @@ func testModel_LabelsFromFile(t *testing.T, tensorFlow *Model) {
if len(result) > 0 {
assertContainsAny(t, result[0].Name, []string{"cat", "kitty"})
//assert.Equal(t, 60, result[0].Uncertainty)
}
})
t.Run(testName("green.jpg"), func(t *testing.T) {
@@ -287,8 +332,6 @@ func testModel_LabelsFromFile(t *testing.T, tensorFlow *Model) {
if len(result) > 0 {
assert.Equal(t, "outdoor", result[0].Name)
//assert.Equal(t, 70, result[0].Uncertainty)
}
})
t.Run(testName("not existing file"), func(t *testing.T) {
@@ -348,7 +391,6 @@ func testModel_Run(t *testing.T, tensorFlow *Model) {
if len(result) > 0 {
assert.Contains(t, result[0].Name, "chameleon")
//assert.Equal(t, 100-93, result[0].Uncertainty)
}
}
})
@@ -376,7 +418,6 @@ func testModel_Run(t *testing.T, tensorFlow *Model) {
if len(result) > 0 {
assertContainsAny(t, result[0].Name, []string{"dog", "corgi"})
//assert.Equal(t, 34, result[0].Uncertainty)
}
}
})