sovit-123 / fasterrcnn-pytorch-training-pipeline

PyTorch Faster R-CNN Object Detection on Custom Dataset

sovit-123/fasterrcnn-pytorch-training-pipeline Issues

dataset.py error?
Closed 13 days ago1
how tu use other model
Updated 14 days ago2
Deformable Convolutional Network
Updated 14 days ago1
small objects detection
Updated 16 days ago2
Reshape error after onnx conversion
Updated 18 days ago12
Background image for Faster RCNN
Closed 19 days ago7
Onnx conversion problem
Updated 20 days ago1
Cannot load the weights after training with custom data
Updated 21 days ago9
ValueError: 'baseball bat' is not in list
Closed a month ago1
dataset used for faster r cnn
Updated a month ago
predections
Updated a month ago2
'log.json' file contains incorrect bounding boxes
Updated 2 months ago2
file names not logged when using option --log-json
Closed 2 months ago3
Confusion matrix, Precision-recall curve, F1 curve; Precision, recall and confidence curve
Updated 2 months ago1
precision recall curve
Updated 2 months ago3
confusion matrix
Updated 2 months ago5
Custom Image Preprocessing
Updated 2 months ago36
Integrate PyGAD genetic algorithm
Updated 3 months ago3
COCO detetction Dataset
Updated 4 months ago2
training on cpu stuck in first epoch
Updated 4 months ago1
How to update maxDets parameter?
Updated 4 months ago
model save error
Updated 5 months ago7
Multinode run problem
Closed 5 months ago4
Selection of the number of --batch sizes for the training process
Closed 5 months ago2
TypeError: __init__() got an unexpected keyword argument 'weights'
Closed 5 months ago4
about VOC2007 dataset training
Closed 5 months ago3
raise ValueError(f"Expected {name} for bbox {bbox} to be in the range [0.0, 1.0], got {value}.")
Updated 5 months ago1
macOS support
Updated 5 months ago1
initialization error
Updated 5 months ago2
how to choose the backbone?
Updated 6 months ago1
What does the output mean when I convert to onnx?
Updated 6 months ago5
Please, help to make the web interface using Flask library
Updated 6 months ago1
raise ValueError(f"Expected {name} for bbox {bbox} to be in the range [0.0, 1.0], got {value}.") ValueError: Expected x_min for bbox (tensor(1.0102), tensor(0.5781), tensor(1.), tensor(0.7539), tensor(4)) to be in the range [0.0, 1.0], got 1.010156273841858.
Closed 6 months ago1
self.eval_imgs[iou_type] = np.concatenate(self.eval_imgs[iou_type], 2) File "<__array_function__ internals>", line 200, in concatenate
Closed 6 months ago6
About background class
Updated 8 months ago1
Validation mAP not consistent
Updated 8 months ago34
How can I properly resume my training?
Updated 8 months ago3
NotImplementedError: Could not run 'torchvision::nms' with arguments from the 'CUDA' backend.
Closed 8 months ago6
Faster RCNN init error
Updated 8 months ago23
What does this output mean?
Updated 9 months ago9
Add Inception Backbone
Updated 9 months ago1
Add VGG16
Closed 9 months ago4
iou metrics
Updated 9 months ago1
Inference Time
Updated 9 months ago2
Question: ResNet50 Backbone weights
Closed 9 months ago5
Defining augmentations
Closed 10 months ago10
Albumentations bouning box error
Updated 10 months ago3
can you add option to save the output to google drive directly
Closed 10 months ago6
can you add image caching
Closed 10 months ago4
what gives me best accuracy of theses models for small object
Closed 10 months ago2