import os import shutil import subprocess from PIL import Image import directories as Dir def clearDir(): #/text_detection/cookie/user_input #shutil.rmtree('/cookie') #os.remove("/cookie/user_input.jpg") #cropped_img_path = "/runs/detect/" + cropped_img_folder_name shutil.rmtree(Dir.cropped_img_path) #'/runs/detect/user_output' #txt_file_path = "/HCR/TextRecognition/log_demo_result.txt" os.remove(Dir.txt_file_path) def textDetection(im): #change dir to yolo folder #yolo_dir = "/HCR/TextDetection/" #subprocess.call('pwd', shell=True) #subprocess.call('ls', shell=True) ## subprocess.call('sudo cd '+ Dir.yolo_dir, shell=True) #transfrom ndarray type to PIL type im = Image.fromarray(im) # save input image to cookie folder ## subprocess.call('cd cookie', shell=True) im.save("/home/user/app"+Dir.yolo_dir+"/cookie/user_input.jpg", 'JPEG') #yolo_dir = "/HCR/TextDetection/" ## subprocess.call('cd '+ Dir.yolo_dir, shell=True) # (Shell) run detect.py to get cropped word images subprocess.call(['python', "/home/user/app"+Dir.yolo_dir+'/detect.py', #User Input Data : /text_detection/cookie '--source','/cookie', #Text Detection Model : /runs/wordDetection/weights/best.pt '--weights', Dir.detect_model_dir, '--conf','0.25', #Output Images Save Directory /runs/detect/user_output '--name', Dir.cropped_img_folder_name, '--save-crop', '--save-conf']) #g = (size / max(im.size)) # gain #im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS) # resize #results = model(im) # inference #results.render() # updates results.imgs with boxes and labels #return Image.fromarray(results.imgs[0]) def textRearrange(): ## subprocess.call('cd ' + Dir.DBSCAN_dir, shell=True) subprocess.call(['python', "/home/user/app"+Dir.DBSCAN_dir+'/DBSCAN.py']) def textRecognition(): #%cd /content/drive/MyDrive/KITA/Text/lmdb/deep-text-recognition-benchmark ## subprocess.call('cd '+Dir.recog_dir, shell=True) #!CUDA_VISIBLE_DEVICES=0 python3 demo.py --Transformation TPS --FeatureExtraction ResNet --SequenceModeling BiLSTM --Prediction Attn --image_folder /content/drive/MyDrive/KITA/Text/YOLO/runs/detect/youtube_data2/crops/word --saved_model /content/drive/MyDrive/KITA/Text/best_accuracy_s/best_accuracy_s.pth subprocess.call('CUDA_VISIBLE_DEVICES="" python3 '+ "/home/user/app"+ Dir.recog_dir +'/demo.py --Transformation TPS --FeatureExtraction ResNet --SequenceModeling BiLSTM --Prediction Attn --image_folder /home/user/app' + Dir.yolo_dir + Dir.cropped_img_path + '/crops/word --saved_model '+ Dir.recog_model_dir, shell=True) def getHcrResult(file_path):#*# texts = "" with open(file_path, 'r') as file: lines = file.readlines() for line in lines[3:]: line = line.replace("\t","*",1) line = line.replace(" ","*",1) parts = line.replace(" ","") parts2 = parts.split("*",2) #print(len(parts2)) texts = texts +" "+ str(parts2[1:2])[2:-2] return texts