Calculating the F score of Object Detection of Mask RCNN
I am using Detectron2 Mask RCNN for an object detection problem. The images consist of cells that are very close to each other. I can not use mAP as a performance measure since the annotations are a bit off from the original location and the prediction is actually more accurate and when I use mAP it will give bad results.
How can I get testing accuracy using tensorboard for Detectron2?
# training Detectron2 from detectron2.engine import DefaultTrainer from detectron2.config import get_cfg ...
Detectron2 Alteranatives - Data Science Stack Exchange
2020年10月13日 · Detectron2 is really good and it supports large number of models / but not all. Eg. Yolo. Do we have alternative to detectron2 which provide easy to use API for both model inference and retraining? just like huggingface transformers for NLP.
Is there a way to set different confidence thresholds for different ...
2022年5月28日 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.
How to convert horizontal bounding box coordinates to oriented …
2021年11月16日 · Built-in faster rcnn network in detectron2 is actually compatible with OBB but I could not make that model work with DOTA. Because I could not convert DOTA box annotations to (cx, cy, w, h, a) . In DOTA, objects are annotated by coordinates of 4 corners which are (x1,y1,x2,y2,x3,y3,x4,y4) .
Why does Faster R-CNN use SGD optimizer instead of Adam?
2020年8月27日 · I just start learning Faster R-CNN and I have some doubts about the optimizer of this network. In my understanding, Adam optimizer performs much better than SGD in a lot of networks.
classification - Jupyter, Python: the kernel appears to have died …
2021年5月7日 · I am training my model on almost 200 000 images, i'm using Jupyter and now after 3 days of training ( i used 800 epochs and batch-size = 600) I have this " the kernel appears to have died.
deep learning - Loss is coming very high for object detection
2021年11月9日 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.
Creating a custom dataset for object detection
2020年3月1日 · Train in Detectron2 / pyTorch ; I have 2 questions: Given that the environment is somewhat consistent throughout all samples, is there a ballpark number / rule of thumb for a decent number of samples to use per class? (100 train / 100 test)? This is a proof of concept project, so I'm just looking for something with reasonable accuracy (80%+)
what is darknet and why is it needed for YOLO object detection?
2020年1月6日 · Darknet is mainly for Object Detection, and have different architecture, features than other deep learning frameworks.