How do we get these numbers,Why aren't they the same with ImageNet's norm_cfg? ImageNet's norm_cfg :mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225] xvjiaruiclosed this ascompletedNov 18, 2020 wjkim81pushed a commit to wjkim81/mmsegmentation that referenced this issueDec 3, ...
Hi there, thanks for building this great toolbox. I was trying to train my detector on the PASCAL VOC dataset. I noticed that the image normalization parameter - std values in ssd512_voc.py and ssd300_voc.py img_norm_cfg = dict(mean=[123...
_img_metas = { 'ori_shape': (480, 640, 3), 'img_shape': (480, 640, 3), 'pad_shape': (480, 640, 3), 'scale_factor': [1., 1., 1., 1.], 'flip': True, 'flip_direction': 'horizontal', 'img_norm_cfg': { 'mean': [123.675, 116.28 , 103.53 ], 'std': [58.395,...
clip_grad_norm_( trainable_params, cfg.solver.max_grad_norm, ) optimizer.step() lr_scheduler.step() optimizer.zero_grad() vis_steps = 500 if not cfg.debug else 20 if global_step % vis_steps == 0: if accelerator.is_main_process: save_dir = f"{cfg.output_dir}/{...
grad_norm.py imgproc.py parallel.py sample.py sample_img2img.py sample_sd3.py train.py train_dreambooth_sd3.py transport.py lumina_t2i .gitignore .isort.cfg .pre-commit-config.yaml LICENSE README.md README_cn.md pyproject.toml requirements.txtBreadcrumbs...
conv1=nn.Conv2d(3,64,kernel_size=7,stride=2,padding=3,bias=False)bn1=nn.BatchNorm2d(64)relu=nn.ReLU(inplace=True)maxpool=nn.MaxPool2d(kernel_size=3,stride=2,padding=1)layer1=self._make_layer(block,64,layers[0])layer2=self._make_layer(block,128,layers[1],stride=2)layer3=self...
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from alignment import norm_crop, norm_crop_with_M from swap_face_fine.Blender.inference import BlenderInfer def get_obj_from_str(string, reload=False): module, cls = string.rsplit(".", 1) if reload: module_imp = importlib.import_module(module) ...
x, grab_v_norm) + grab_h_pixels, bb.Max.y); @@ -1579,12 +1579,12 @@ bool ImGui::BeginCombo(const char* label, const char* preview_value, ImGuiComboF const float value_x2 = ImMax(frame_bb.Min.x, frame_bb.Max.x - arrow_size);...
module_output.num_batches_tracked=module.num_batches_trackedforname,childinmodule.named_children():module_output.add_module(name,_convert_batchnorm(child))delmodulereturnmodule_outputdef_demo_mm_inputs(input_shape,num_classes):"""Create a superset of inputs needed to run test or train batches....