yolov7
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Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
YOLO v7 ![image](https://user-images.githubusercontent.com/45539173/180390528-63c9e0bf-4daf-4c33-99de-564f763d16fa.png) YOLOv5 ![image](https://user-images.githubusercontent.com/45539173/180390622-7a7f6fc7-0053-4984-96ee-891acd447c61.png) Hi, this code differs from yolov5. I think **m.anchors** should not be divided by the **m.stride** before running **check_anchor_order**, and that sorting should be done...
I tried to do a comparison of inference speed with yolov7 and yolov5m trained on a custom dataset running on Tesla T4 16GB gpu. The paper claims that yolov7 should...
I'm currently using the latest version of the codebase. I fine-tuned a yolov7 model on a custom dataset starting from the yolov7_training.pt weights. My dataset is a single class so...
Pytorch: 1.12, tensorrt:8.2.1, onnx version:12 (Works well when I use the 80cls yolov7) I convert the yolov7.pt (based on COCO but 5 extra classes added, 85 classes total.) to yolov7.onnx...
i didn't read the detail code, but when i use the script(detect.py) to filter image with person, the memory(64G in my PC, but it will be exhausted fully) will increase...
The provided yolov7-w6-pose.pt is well used. I tried to export the onnx model with python export.py --weights 'yolov7-w6-pose.pt' --simplify I tried to infer the model with the exported model, the...
Traceback (most recent call last): File "E:\Item\Item_done\yolo\yolo5\yolov7\yolov7-main\pose.py", line 27, in output = output_to_keypoint(output) File "E:\Item\Item_done\yolo\yolo5\yolov7\yolov7-main\utils\plots.py", line 443, in output_to_keypoint targets.append([i, cls, *list(*xyxy2xywh(np.array(box)[None])), conf, *list(kpts.cpu().numpy()[index])]) RuntimeError: Can't call numpy() on Tensor...
I tried to export the PyTorch model to ONNX using `python export.py --weights yolov7-tiny.pt --grid --end2end --simplify --topk-all 100 --iou-thres 0.65 --conf-thres 0.35 --img-size 640 640 --max-wh 640` and then...
This PR is intended to export model from PyTorch to `onnx`, and then serialize the exported onnx model to native TRT engine, which will be inferred using TensorRT I.E, -...