From f6279b074be462f3659267dbf0914a525a3ba87e Mon Sep 17 00:00:00 2001
From: Anders Langlie <andeslan@stud.ntnu.no>
Date: Wed, 3 Mar 2021 09:52:49 +0100
Subject: [PATCH] Included sex_identification. Currently run from seperate
file.
---
.gitignore | 3 +-
algorithm/train_src/isolated_sex_ident.py | 3 ++
algorithm/train_src/sex_identification.py | 50 +++++++++++++++++++++++
algorithm/train_src/test_straightening.py | 3 +-
run.py | 1 -
5 files changed, 56 insertions(+), 4 deletions(-)
create mode 100644 algorithm/train_src/isolated_sex_ident.py
create mode 100644 algorithm/train_src/sex_identification.py
diff --git a/.gitignore b/.gitignore
index c12b113..e25c1ed 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,4 +5,5 @@ __pycache__
algorithm/train_src/dlc_model
img_analyze/*.png
env
-temp_images
\ No newline at end of file
+temp_images
+algorithm/train_src/imageai_model
\ No newline at end of file
diff --git a/algorithm/train_src/isolated_sex_ident.py b/algorithm/train_src/isolated_sex_ident.py
new file mode 100644
index 0000000..19f4e2b
--- /dev/null
+++ b/algorithm/train_src/isolated_sex_ident.py
@@ -0,0 +1,3 @@
+import sex_identification
+
+print(sex_identification.identify("E:/PycharmProjects/salamander-api/img_analyze/female.png"))
\ No newline at end of file
diff --git a/algorithm/train_src/sex_identification.py b/algorithm/train_src/sex_identification.py
new file mode 100644
index 0000000..708a4ba
--- /dev/null
+++ b/algorithm/train_src/sex_identification.py
@@ -0,0 +1,50 @@
+from imageai.Detection.Custom import DetectionModelTrainer, CustomObjectDetection
+import os
+import tensorflow as tf
+
+
+def identify(image):
+ config = tf.compat.v1.ConfigProto()
+ config.gpu_options.allow_growth = True
+ session = tf.compat.v1.Session(config=config)
+
+ root_path = "../../../salamander-api"
+ os_directory_path = os.path.abspath(root_path)
+
+ image_detector = CustomObjectDetection()
+ image_detector.setModelTypeAsYOLOv3()
+ image_detector.setModelPath(os.path.join(os_directory_path,
+ "algorithm/train_src/imageai_model/models/detection_model-ex-012--loss-0018.483.h5"))
+ image_detector.setJsonPath(
+ os.path.join(os_directory_path, "algorithm/train_src/imageai_model/json/detection_config.json"))
+ image_detector.loadModel()
+
+ predictions = image_detector.detectObjectsFromImage(input_image=image,
+ output_image_path=os.path.join(os_directory_path,
+ "img_analyze/detected_salamander.png"),
+ minimum_percentage_probability=40)
+ # winner = {"name": "male", "percentage_probability": 0}
+ # for prediction in predictions:
+ # if prediction['percentage_probability'] > winner['percentage_probability']:
+ # winner['percentage_probability'] = prediction['percentage_probability']
+ # winner['name'] = prediction['name']
+
+ largest_p = max(predictions, key=lambda x: x['percentage_probability'])['name']
+ return largest_p
+
+
+def train():
+ config = tf.compat.v1.ConfigProto()
+ config.gpu_options.allow_growth = True
+ session = tf.compat.v1.Session(config=config)
+
+ directory_path = "../../../salamander-api/img_analyze"
+ os_directory_path = os.path.abspath(directory_path)
+
+ trainer = DetectionModelTrainer()
+ trainer.setModelTypeAsYOLOv3()
+ trainer.setDataDirectory(data_directory=os.path.join(os_directory_path, "algorithm/train_src/imageai_model"))
+ trainer.setTrainConfig(object_names_array=["male", "female"], batch_size=8, num_experiments=200)
+ # In the above,when training for detecting multiple objects,
+ # set object_names_array=["object1", "object2", "object3",..."objectz"]
+ trainer.trainModel()
diff --git a/algorithm/train_src/test_straightening.py b/algorithm/train_src/test_straightening.py
index ca88690..1a8f637 100644
--- a/algorithm/train_src/test_straightening.py
+++ b/algorithm/train_src/test_straightening.py
@@ -6,7 +6,7 @@ import matplotlib.pyplot as plt
config_path= "dlc_model/config.yaml"
directory_path= "../../../salamander-api/img_analyze"
-image_to_predict = "img40.png"
+image_to_predict = "female.png"
config = os.path.abspath(config_path)
os_directory_path = os.path.abspath(directory_path)
@@ -14,7 +14,6 @@ image_type = image_to_predict[-4:]
img_directory = os_directory_path + '\\' + image_to_predict
smallpath = os_directory_path + '/' + 'small' + image_to_predict
-
# reading image:
img = cv2.imread(img_directory)
# You will have to convert the color if you use OpenCV.
diff --git a/run.py b/run.py
index e513e14..6e51c1a 100644
--- a/run.py
+++ b/run.py
@@ -1,5 +1,4 @@
from api import app
-
if __name__ == "__main__":
app.run(debug=True, host='0.0.0.0')
--
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