estimage code

.gitignore

@@ -3,6 +3,8 @@ venv
 images
 __pycache__
 algorithm/train_src/dlc_model
+algorithm/train_src/imageai_model
 img_analyze/*.png
 env
 temp_images
+*.db
\ No newline at end of file

algorithm/train_src/estimate_gender.py

@@ -166,6 +166,8 @@ def estimate_image(detection_model_path: str = abs_path_imageai_model,
 	:return detected_objects_image_array:
 	"""
     with _ACCESS_TF_AND_GPU_SEMA:
+        gender = "AI_sex"
+        if os.path.isfile(detection_model_path) and os.path.isfile(configuration_json):
             manager = Manager()
             return_dict = manager.list()
             # return_dict =  multiprocessing.Value("d", [], lock=False)
@@ -177,8 +179,10 @@ def estimate_image(detection_model_path: str = abs_path_imageai_model,
             p = Process(target=run_estimation, args=args)
             p.start()
             p.join()
-        return return_dict[0], return_dict[1], return_dict[2], return_dict[3]
-
+            if return_dict[0]['name']:
+                gender = return_dict[0]['name']
+            return gender, return_dict[1], return_dict[2], return_dict[3]
+        return gender, None, None, None
 
 class BoundBox:
     def __init__(self, xmin, ymin, xmax, ymax, objness=None, classes=None):

api/endpoints/findsalamanderinfo.py

@@ -7,7 +7,7 @@ import cv2
 import os
 from api import limiter
 from image_encoder.image_encoder import *
-from path_constants import image_type
+from path_constants import image_type, abs_path_imageai_model, abs_path_imageai_config
 ALLOWED_EXTENSIONS = ['jpg', 'png', 'jpeg']
 
 
@@ -38,7 +38,8 @@ class FindSalamanderInfo(Resource):
                     str_image = cv2.cvtColor(str_image, cv2.COLOR_BGR2RGB)
                     cv2.imwrite(os.path.join(temp_img_path, str(user_id) + "_str." + image_type), str_image)
                     encoded = encode(os.path.join(temp_img_path, str(user_id) + "_str." + image_type))[2:-1]
-                    return jsonify({"sex": "AI_sex", "species": "AI_species", "status": 200, "image": encoded})
+                    gender, _, _, _ = estimate_image(abs_path_imageai_model,abs_path_imageai_config)
+                    return jsonify({"sex": gender, "species": "AI_species", "status": 200, "image": encoded})
 
                 else:
                     return jsonify({"message": "image could not be processed", "status": 400})