Commit dfdeb8b3 authored by Micaela Verucchi's avatar Micaela Verucchi
Browse files

Modify weights download for some nets, now also calibration tables are downloaded in tests folder



Signed-off-by: default avatarMicaela Verucchi <micaelaverucchi@gmail.com>
parent e4900120
......@@ -183,17 +183,18 @@ cd build
| yolo_tiny | YOLO v2 tiny<sup>1</sup> | [COCO 2014](http://cocodataset.org/) | 80 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/m3orfJr8pGrN5mQ/download) |
| yolo_voc | YOLO v2<sup>1</sup> | [VOC ](http://host.robots.ox.ac.uk/pascal/VOC/) | 21 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/DJC5Fi2pEjfNDP9/download) |
| yolo3 | YOLO v3<sup>2</sup> | [COCO 2014](http://cocodataset.org/) | 80 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/jPXmHyptpLoNdNR/download) |
| yolo3_512 | YOLO v3<sup>2</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/R6qSLfFAF9F2ni9/download) |
| yolo3_berkeley | YOLO v3<sup>2</sup> | [BDD100K ](https://bair.berkeley.edu/blog/2018/05/30/bdd/) | 10 | 320x544 | [weights](https://cloud.hipert.unimore.it/s/o5cHa4AjTKS64oD/download) |
| yolo3_coco4 | YOLO v3<sup>2</sup> | [COCO 2014](http://cocodataset.org/) | 4 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/o27NDzSAartbyc4/download) |
| yolo3_flir | YOLO v3<sup>2</sup> | [FREE FLIR](https://www.flir.com/oem/adas/adas-dataset-form/) | 3 | 320x544 | [weights](https://cloud.hipert.unimore.it/s/62DECncmF6bMMiH/download) |
| yolo3_tiny | YOLO v3 tiny<sup>2</sup> | [COCO 2014](http://cocodataset.org/) | 80 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/LMcSHtWaLeps8yN/download) |
| yolo3_tiny512 | YOLO v3 tiny<sup>2</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/wRW9nmkibSe5HoS/download) |
| yolo3_tiny512 | YOLO v3 tiny<sup>2</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/8Zt6bHwHADqP4JC/download) |
| dla34 | Deep Leayer Aggreagtion (DLA) 34<sup>3</sup> | [COCO 2014](http://cocodataset.org/) | 80 | 224x224 | weights |
| dla34_cnet | Centernet (DLA34 backend)<sup>4</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/8AjXdgCeRzCa5AF/download) |
| dla34_cnet | Centernet (DLA34 backend)<sup>4</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/5qpxTcCPn4b79wX/download) |
| mobilenetv2ssd | Mobilnet v2 SSD Lite<sup>5</sup> | [VOC ](http://host.robots.ox.ac.uk/pascal/VOC/) | 21 | 300x300 | [weights](https://cloud.hipert.unimore.it/s/x4ZfxBKN23zAJQp/download) |
| mobilenetv2ssd512 | Mobilnet v2 SSD Lite<sup>5</sup> | [COCO 2017](http://cocodataset.org/) | 81 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/x4ZfxBKN23zAJQp/download) |
| mobilenetv2ssd512 | Mobilnet v2 SSD Lite<sup>5</sup> | [COCO 2017](http://cocodataset.org/) | 81 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/pdCw2dYyHMJrcEM/download) |
| resnet101 | Resnet 101<sup>6</sup> | [COCO 2014](http://cocodataset.org/) | 80 | 224x224 | weights |
| resnet101_cnet | Centernet (Resnet101 backend)<sup>4</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/Ye8f5JJPRo9AxCi/download) |
| resnet101_cnet | Centernet (Resnet101 backend)<sup>4</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 512x512 | [weights](https://cloud.hipert.unimore.it/s/SdjBz6xnKRQNTQ7/download) |
| csresnext50-panet-spp | Cross Stage Partial Network <sup>7</sup> | [COCO 2014](http://cocodataset.org/) | 80 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/Kcs4xBozwY4wFx8/download) |
......
......@@ -103,7 +103,7 @@ const char *output_bin[]={
int main()
{
downloadWeightsifDoNotExist(input_bin, "../tests/dla34_cnet", "https://cloud.hipert.unimore.it/s/8AjXdgCeRzCa5AF/download");
downloadWeightsifDoNotExist(input_bin, "../tests/dla34_cnet", "https://cloud.hipert.unimore.it/s/5qpxTcCPn4b79wX/download");
// Network layout
tk::dnn::dataDim_t dim(1, 3, 512, 512, 1);
......
......@@ -134,7 +134,7 @@ const char *regression_header5 = "../tests/mobilenetv2ssd512/layers/regression_h
int main()
{
downloadWeightsifDoNotExist(input_bin, "../tests/mobilenetv2ssd512", "https://cloud.hipert.unimore.it/s/Ye8f5JJPRo9AxCi/download");
downloadWeightsifDoNotExist(input_bin, "../tests/mobilenetv2ssd512", "https://cloud.hipert.unimore.it/s/pdCw2dYyHMJrcEM/download");
int classes = 81;
......
......@@ -185,7 +185,7 @@ const char *output_bin[]={
int main()
{
downloadWeightsifDoNotExist(input_bin, "../tests/resnet101_cnet", "https://cloud.hipert.unimore.it/s/B6mj33k7beECXsY/download");
downloadWeightsifDoNotExist(input_bin, "../tests/resnet101_cnet", "https://cloud.hipert.unimore.it/s/SdjBz6xnKRQNTQ7/download");
// Network layout
tk::dnn::dataDim_t dim(1, 3, 512, 512, 1);
......
......@@ -10,7 +10,7 @@ int main() {
// create yolo3 model
std::string bin_path = "../tests/yolo3_512";
downloadWeightsifDoNotExist("../tests/yolo3_512/layers/input.bin", bin_path, "https://cloud.hipert.unimore.it/s/39XbxMxaX7zwFKQ/download");
downloadWeightsifDoNotExist("../tests/yolo3_512/layers/input.bin", bin_path, "https://cloud.hipert.unimore.it/s/R6qSLfFAF9F2ni9/download");
int classes = 80;
tk::dnn::Yolo *yolo [3];
#include "models/Yolo3.h"
......
......@@ -23,7 +23,7 @@ const char *output_bin = "../tests/yolo3_tiny512/debug/layer23_out.bin";
int main() {
downloadWeightsifDoNotExist(input_bin, "../tests/yolo3_tiny512", "https://cloud.hipert.unimore.it/s/wRW9nmkibSe5HoS/download");
downloadWeightsifDoNotExist(input_bin, "../tests/yolo3_tiny512", "https://cloud.hipert.unimore.it/s/8Zt6bHwHADqP4JC/download");
int classes = 80;
......
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment