def getModel():
global prediction
if prediction is not None:
return prediction
prediction = CustomImagePrediction()
prediction.setModelTypeAsResNet50()
prediction.setModelPath("model.h5")
prediction.setJsonPath("styles.json")
prediction.loadModel(num_objects=25)
return prediction
from imageai.Prediction.Custom import CustomImagePrediction
import os
execution_path = os.getcwd()
prediction = CustomImagePrediction()
prediction.setModelTypeAsResNet50()
prediction.setModelPath(
os.path.join(execution_path,
"./dataset/models/try2_model_ex-006_acc-0.714195.h5"))
prediction.setJsonPath(
os.path.join(execution_path, "./dataset/json/model_class.json"))
prediction.loadModel(num_objects=25)
predictions, probabilities = prediction.classifyImage(os.path.join(
execution_path, "./dataset/train/queenAnne/144_800px-Isbister_School.jpg"),
result_count=25)
for eachPrediction, eachProbability in zip(predictions, probabilities):
print(eachPrediction, " : ", eachProbability)
