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JavaJDK1.8适配 完成从摄像头中检测动物

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Signed-off-by: JoeAllen <2494136784@qq.com>
This commit is contained in:
JoeAllen
2022-07-29 09:13:20 +08:00
parent 41179c52b2
commit 2c8c05dedf
5 changed files with 36 additions and 126 deletions
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src/main/java/cn/heavenlybook/utils/AnimalsClassification.java
+19 -17
View File
@@ -59,25 +59,27 @@ public final class AnimalsClassification {
return new Classifications(names, probs);
}
static Criteria<Image, Classifications> criteria;
static ZooModel<Image, Classifications> rotateModel;
static Predictor<Image, Classifications> classifier;
public static Classifications classfier(Image img)
throws IOException, ModelException, TranslateException {
Criteria<Image, Classifications> criteria =
Criteria.builder()
.optEngine("PaddlePaddle")
.setTypes(Image.class, Classifications.class)
.optModelUrls("https://aias-home.oss-cn-beijing.aliyuncs.com/models/animals.zip")
// .optModelUrls("/Users/calvin/model/animals/")
.optModelName("inference")
.optTranslator(new AnimalTranslator())
.optProgress(new ProgressBar())
.build();
try (ZooModel<Image, Classifications> rotateModel = ModelZoo.loadModel(criteria)) {
try (Predictor<Image, Classifications> classifier = rotateModel.newPredictor()) {
Classifications classifications = classifier.predict(img);
return classifications;
}
}
criteria =
criteria == null
? Criteria.builder()
.optEngine("PaddlePaddle")
.setTypes(Image.class, Classifications.class)
.optModelUrls("https://aias-home.oss-cn-beijing.aliyuncs.com/models/animals.zip")
// .optModelUrls("/Users/calvin/model/animals/")
.optModelName("inference")
.optTranslator(new AnimalTranslator())
.optProgress(new ProgressBar())
.build()
: criteria;
rotateModel = rotateModel == null ? ModelZoo.loadModel(criteria) : rotateModel;
classifier = classifier == null ? rotateModel.newPredictor() : classifier;
return classifier.predict(img);
}
}
src/main/java/cn/heavenlybook/utils/LightAnimalsClassification.java
+4 -2
View File
@@ -37,7 +37,9 @@ public final class LightAnimalsClassification {
Classifications.Classification item = items.get(i);
double prob = item.getProbability();
probArr[i] = prob;
if (prob > max) max = prob;
if (prob > max) {
max = prob;
}
}
for (int i = 0; i < items.size(); i++) {
@@ -69,7 +71,7 @@ public final class LightAnimalsClassification {
.optProgress(new ProgressBar())
.build();
try (ZooModel rotateModel = ModelZoo.loadModel(criteria)) {
try (ZooModel<Image, Classifications> rotateModel = ModelZoo.loadModel(criteria)) {
try (Predictor<Image, Classifications> classifier = rotateModel.newPredictor()) {
Classifications classifications = classifier.predict(img);
return classifications;