From 0a03a66b1ec703e7e835b8deab701523bfa9cc5d Mon Sep 17 00:00:00 2001
From: JsPatenaude <jean-sebastien.patenaude@polymtl.ca>
Date: Sat, 4 Apr 2020 18:47:33 -0400
Subject: [PATCH] ignore th 6s in dataset
---
.../armor_digit/baseline_experiments.py | 37 ++++++++++++-------
.../research/dataset/armor_dataset_factory.py | 25 +++++--------
2 files changed, 32 insertions(+), 30 deletions(-)
diff --git a/robots-at-robots/research/armor_digit/baseline_experiments.py b/robots-at-robots/research/armor_digit/baseline_experiments.py
index 8768336..92dcc29 100644
--- a/robots-at-robots/research/armor_digit/baseline_experiments.py
+++ b/robots-at-robots/research/armor_digit/baseline_experiments.py
@@ -7,6 +7,8 @@ from tensorflow.keras.utils import to_categorical
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPooling2D
+from sklearn.model_selection import train_test_split
+
IMG_SIZE = 28
DATASET_SPLIT_FACTOR = 5
N_CLASSES = 10
@@ -39,10 +41,13 @@ def load_digits_img_to_data():
# TODO but before, we use this hardcoded path...
path = '.\\..\\..\\..\\dataset\\dji_roco\\robomaster_Final Tournament\\digits_found'
digits_found = os.listdir(path)
- features_train = []
- label_train = []
- features_test = []
- label_test = []
+ # features_train = []
+ # label_train = []
+ # features_test = []
+ # label_test = []
+
+ all_features = []
+ all_labels = []
for i, img_file in enumerate(digits_found):
img_file_name = os.path.join(path, img_file)
@@ -52,18 +57,25 @@ def load_digits_img_to_data():
# split datatset into training and test
# TODO use the train_test_split or see https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html
- if i % DATASET_SPLIT_FACTOR == 0:
- features_test.append(digit_res)
- label_test.append(img_file[-5])
- else:
- features_train.append(digit_res)
- label_train.append(img_file[-5])
+ # if i % DATASET_SPLIT_FACTOR == 0:
+ # features_test.append(digit_res)
+ # label_test.append(img_file[-5])
+ # else:
+ # features_train.append(digit_res)
+ # label_train.append(img_file[-5])
+
+ all_features.append(digit_res)
+ all_labels.append(img_file[-5])
# cv2.imshow('img', digit_res)
# k = cv2.waitKey(0) & 0xFF
# if k == 27:
# break
# cv2.destroyAllWindows()
+
+ features_train, features_test, label_train, label_test = train_test_split(
+ all_features, all_labels, test_size=0.1)
+
return np.array(features_train), np.array(label_train), np.array(features_test), np.array(label_test)
@@ -112,11 +124,8 @@ def training_model(features_train, label_train, features_test, label_test):
if __name__ == "__main__":
digits_features_train, digits_label_train, digits_features_test, digits_label_test = load_digits_img_to_data()
- # TODO fct to split data into train and test
for img in digits_label_train:
- # plt.imshow(img, cmap='Greys')
- # plt.show()
print('train', img)
for img in digits_label_test:
print('test', img)
- training_model(digits_features_train, digits_label_train, digits_features_test, digits_label_test)
+ # training_model(digits_features_train, digits_label_train, digits_features_test, digits_label_test)
diff --git a/robots-at-robots/research/dataset/armor_dataset_factory.py b/robots-at-robots/research/dataset/armor_dataset_factory.py
index 5fc5289..60db019 100644
--- a/robots-at-robots/research/dataset/armor_dataset_factory.py
+++ b/robots-at-robots/research/dataset/armor_dataset_factory.py
@@ -14,7 +14,7 @@ from research_common.dataset.roco_dataset import ROCODataset
class ArmorDatasetFactory:
@staticmethod
def from_image_annotation(
- image_annotation: ImageAnnotation,
+ image_annotation: ImageAnnotation,
) -> Iterable[Tuple[Image, ArmorColor, ArmorNumber, int, Path]]:
img = image_annotation.image
armors: List[Armor] = TypeObjectValidator(ObjectType.Armor).filter(image_annotation.objects, img)
@@ -31,22 +31,15 @@ class ArmorDatasetFactory:
def save_digits_img():
for j, (digit_img, c, n, k, p) in enumerate(ArmorDatasetFactory.from_dataset(DJIROCODataset.Final)):
- print(c, n, k, 'in', p)
- plt.imshow(digit_img)
- plt.savefig(str(p.parents[1]) + '\\digits_found\\digit' + str(j) + '_' + c.name + '_' + str(n) + '.png')
- plt.clf()
-
- if j == 50:
- break
+ # we ignore the 6, because the format of their pictures is not accurate and we don't need them
+ if n != 6:
+ if j >= 50:
+ break
+ print(c, n, k, 'in', p)
+ plt.imshow(digit_img)
+ plt.savefig(str(p.parents[1]) + '\\digits_found\\digit' + str(j) + '_' + c.name + '_' + str(n) + '.png')
+ plt.clf()
if __name__ == "__main__":
save_digits_img()
- # for i, (armor_img, c, n, k, p) in enumerate(ArmorDatasetFactory.from_dataset(DJIROCODataset.Final)):
- # print(c, n, k, "in", p)
- # plt.imshow(armor_img)
- # plt.show()
- # plt.clf()
- #
- # if i == 50:
- # break
--
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