View Eigen2CV.h
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
/** | |
* @brief Mapping functions from Eigen data types to OpenCV | |
* @author Eugene Khvedchenya <ekhvedchenya@gmail.com> | |
* @details This header file contains code snippet for easy mapping Eigen types to OpenCV and back with minimal overhead. | |
* @more computer-vision.talks.com/articles/mapping-eigen-to-opencv/ | |
* Features: | |
* - Mapping plain data types with no overhead (read/write access) | |
* - Mapping expressions via evaluation (read only acess) | |
* | |
* Known issues: |
View retina_v2.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
class RetinaNet(nn.Module): | |
RETINA_NET_OUTPUT_BBOXES = "bboxes" | |
RETINA_NET_OUTPUT_SCORES = "scores" | |
... | |
def forward(self, image): | |
x = self.encoder(image) | |
x = self.decoder(x) | |
bboxes, scores = self.head(x) |
View gist:f106e882c757c8929d2a94f4a3b6507f
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from collections import OrderedDict | |
from functools import partial | |
from typing import Union, List, Dict, Tuple, Type | |
from pytorch_toolbelt.modules import ( | |
conv1x1, | |
UnetBlock, | |
ACT_RELU, | |
ABN, | |
ACT_SWISH, |
View detect_anomaly.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import torch | |
def main(): | |
torch.autograd.detect_anomaly() | |
... | |
# Rest of the training code | |
# OR | |
class MyNumericallyUnstableLoss(nn.Module): |
View criterions.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# https://github.com/BloodAxe/Kaggle-2020-Alaska2 | |
callbacks += [ | |
CriterionCallback( | |
input_key=INPUT_TRUE_MODIFICATION_FLAG, | |
output_key=OUTPUT_PRED_MODIFICATION_FLAG, | |
criterion_key="bce" | |
), | |
CriterionCallback( | |
input_key=INPUT_TRUE_MODIFICATION_TYPE, |
View alaska2_dataset.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# https://github.com/BloodAxe/Kaggle-2020-Alaska2/blob/master/alaska2/dataset.py#L373 | |
class TrainingValidationDataset(Dataset): | |
def __init__( | |
self, | |
images: Union[List, np.ndarray], | |
targets: Optional[Union[List, np.ndarray]], | |
quality: Union[List, np.ndarray], | |
bits: Optional[Union[List, np.ndarray]], | |
transform: Union[A.Compose, A.BasicTransform], | |
features: List[str], |
View retina.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Bad practice, don't return tuple | |
class RetinaNet(nn.Module): | |
... | |
def forward(self, image): | |
x = self.encoder(image) | |
x = self.decoder(x) | |
bboxes, scores = self.head(x) | |
return bboxes, scores |
View real-world-case.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# https://github.com/BloodAxe/Kaggle-2020-Alaska2/blob/master/alaska2/models/timm.py#L104 | |
def forward(self, **kwargs): | |
x = kwargs[self.input_key] | |
x = self.rgb_bn(x) | |
x = self.encoder.forward_features(x) | |
embedding = self.pool(x) | |
result = { | |
OUTPUT_PRED_MODIFICATION_FLAG: self.flag_classifier(self.drop(embedding)), | |
OUTPUT_PRED_MODIFICATION_TYPE: self.type_classifier(self.drop(embedding)), |
View normalization_and_loss_on_model.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
class MySegmentationDataset(Dataset): | |
... | |
def __getitem__(self, index): | |
image = cv2.imread(self.images[index]) | |
target = cv2.imread(self.masks[index]) | |
# No data normalization and type casting here | |
return torch.from_numpy(image).permute(2,0,1).contiguous(), | |
torch.from_numpy(target).permute(2,0,1).contiguous() |
View pytorch_data_preload.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
class RAMDataset(Dataset): | |
def __init__(image_fnames, targets): | |
self.targets = targets | |
self.images = [] | |
for fname in tqdm(image_fnames, desc="Loading files in RAM"): | |
with open(fname, "rb") as f: | |
self.images.append(f.read()) | |
def __len__(self): | |
return len(self.targets) |
NewerOlder