from imageai.Prediction import ImagePrediction
import os
import time
#開始計時
start_time=time.time()
execution_path=os.getcwd()
#對ImagePrediction類進行實例化
prediction=ImagePrediction()
#設置算法模型類型
prediction.setModelTypeAsResNet()
prediction.setModelPath(os.path.join(execution_path,'resent50_weights_tf_dim_ordering_tf_kernels.h5'))
prediction.loadModel()
predictions,probabilities=prediction.predictioImage(os.path.join(execution_path,'sample.jpg'),result_count=5)
end_time=time.time()
for eachPrediction,eachProbability in zip(predictions,probabilities):
    print(eachPrediction+":"+str(eachProbability))
print('Total time cost:',end_time-start_time)

#多圖像預測
from image.Prediction import ImagePrediction
import os
execution_path=os.getcwd()
#初始化預測器
multiple_prediction=ImagePrediction()
multiple_prediction.setModelTypeAsResNet()
#設置模型文件路徑
multiple_prediction.setModelPath(os.path.join(execution_path,'resent50_weights_tf_ordering_tf_kernels.h5'))
#加載模型
multiple_prediction.loadModel()
all_images_array=[]
all_files=os.listdir(execution_path)
for each_file in all_files:
    if(each_file.endswith('.jpg') or each_file.endswith('.png')):
        all_images_array.append(each_file)
results_array=multiple_prediction.predictMultipleImages(all_images_array,result_count_per_image=3)
for each_result in results_array:
    predictions,percentage_probanlities=each_result['predictions'],each_result['percentage_probabilities']
    for index in range(len(predictions)):
        print(predictions[index]+':'+str(percentage_probanlities[index]))
print('-----------')

#目標檢測
from imageai.Detection import ObjectDetection
import os
import time
start_time=time.time()
#execution_path=os.getcwd()#獲取當前目錄
detector=ObjectDetection() #實例化一個ObjectDetection類
detector.setModelTypeAsRetinaNet() #設置算法模型類型為RetinaNet
#etector.setModelPath()
detector.loadModel() #加載模型
#圖像目標檢測，百分比概率閾值設置為30可檢測出更多的物體（默認值為30）
detections=detector.detectObjectsFromImage(input_image="D:\Image\\four.jpg",output_image_path='D:\Image\\fourr.jpg',minimum_percentage_probability=30)
end_time=time.time()
for eachObject in detections:
    print(eachObject['name'],":",eachObject['percentage_probability'],":",eachObject['box_points'])
print('Total Time cost:',end_time-start_time)

#視頻目標檢測
from imageai.Detection import VideoObjectDetection
import os
import time
start_time=time.time()
detector=VideoObjectDetection() #初始化視頻檢測類
detector.setModelTypeAsRetinaNet()
#detector.setModelPath('D:\Image:\haha.mp4')
detector.loadModel() #加載模型
video_path=detector.detectObjectsFromVideo(input_file_path='D:\Image\haha.mp4',output_file_path='D:Image:\hahaha.mp4',frames_per_second=20,log_progress=True)
print(video_path)
end_time=time.time()
print('Total time cost:',end_time-start_time)