restructured face_detection and face_rec folders and changed padding color to black

app/__init__.py

@@ -1,18 +1,17 @@
 from flask import Flask,session
 from datetime import timedelta
 
-from app.face_detection import inference as fd
-from app.face_detection.helper import get_crops as fd_get_crops
-from app.face_recognition import inference as fr
-from app.face_recognition.aligner import aligner
-from app.face_recognition import helper as fr_helper
+from face_detection import inference as fd
+from face_detection.helper import get_crops as fd_get_crops
+from face_recognition import inference as fr
+from face_recognition.aligner import aligner
+from face_recognition import helper as fr_helper
 
 
 
-face_detector=fd.face_detection("app/face_detection/Models/v1")
+face_detector=fd.face_detection("face_detection/Models/v1")
 face_detector.square_preprocessing=fd.square_pad()
-# face_recognizer=fr.face_recognition("app/face_recognition/feature_extractor.h5")
-face_recognizer=fr.face_recognition("app/face_recognition/Models/v1")
+face_recognizer=fr.face_recognition("face_recognition/Models/v1")
 aligner_obj=aligner(min_aligner_confidence=0.6)
 
 image_size=544

app/api/routes.py

@@ -1,4 +1,4 @@
-from flask import request,jsonify,g
+from flask import request,jsonify,g,session
 from app.api import bp
 from app.helper import generate_random_id,access_database_as_admin,image_to_base64,base64_to_image,add_row_user_table,read_row_user_table,read_user_table,remove_person_from_user_table
 from PIL import ImageOps,Image

{app/face_detection → face_detection}/create_load_model.py

@@ -1,7 +1,7 @@
 import os
 import tensorflow as tf
 from tensorflow.keras import Model,layers
-from app.face_detection.config import class_names
+from face_detection.config import class_names
 
 os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
 # custom layer for reshaping last layer

{app/face_detection → face_detection}/decode_yolo_v2.py

@@ -4,7 +4,7 @@ from matplotlib.patches import Rectangle
 import copy
 import tensorflow.keras.backend as K
 import cv2
-from app.face_detection.config import cell_size,idx_to_class,class_to_idx,class_colors
+from face_detection.config import cell_size,idx_to_class,class_to_idx,class_colors
 
 
 

{app/face_detection → face_detection}/helper.py

@@ -1,9 +1,10 @@
 import cv2
 import numpy as np
-from app.face_detection.inference import square_pad
+from face_detection.inference import square_pad
 
 
-square_maker=square_pad(color=(255,255,255))
+# square_maker=square_pad(color=(255,255,255))
+square_maker=square_pad(color=(0,0,0))
 def get_crops(img,objs_found,aligner=None,resize:tuple=None):
     img_h,img_w,_=img.shape
     all_crops=[]

{app/face_detection → face_detection}/inference.py

@@ -277,7 +277,7 @@ if __name__=="__main__":
     plt.show()
     # cv2.imwrite("test_output.jpg",pred_img[:,:,::-1])
 else:
-    import app.face_detection.create_load_model as load_model_lib
-    import app.face_detection.decode_yolo_v2 as decode_model_lib
-    from app.face_detection.create_load_model import *
-    from app.face_detection.decode_yolo_v2 import *
+    import face_detection.create_load_model as load_model_lib
+    import face_detection.decode_yolo_v2 as decode_model_lib
+    from face_detection.create_load_model import *
+    from face_detection.decode_yolo_v2 import *

{app/face_recognition → face_recognition}/inference.py

@@ -13,8 +13,8 @@ import importlib
 
 
 
-from app.face_recognition import config
-from app.face_recognition.aligner import  aligner
+from face_recognition import config
+from face_recognition.aligner import  aligner