Comments (4)
thank you for your excellent work!
I saw people met the same problem of data preprocessing on the I3D feature extraction.
Can you share the code of data preprocessing before I3d ?
Can you specify exactly how you do the tenCrop on an image ?
thanks!
Below is my feature extraction setup.
mean = [114.75, 114.75, 114.75]
std = [57.375, 57.375, 57.375]
split == '10_crop_ucf':
transform = transforms.Compose([
gtransforms.GroupResize(256),
gtransforms.GroupTenCrop(224),
gtransforms.ten_crop_ToTensor(),
gtransforms.GroupNormalize_ten_crop(mean, std),
gtransforms.LoopPad(max_len),
])
class GroupTenCrop(object):
def init(self, size):
transform = torchvision.transforms.Compose([
torchvision.transforms.TenCrop(size),
torchvision.transforms.Lambda(lambda crops: torch.stack([torchvision.transforms.ToTensor()(crop) for crop in crops])),
])
self.worker = transform
def call(self, img_group):
return [self.worker(img) for img in img_group]
class ToTensor(object):
def init(self):
self.worker = lambda x: F.to_tensor(x) * 255
def call(self, img_group):
img_group = [self.worker(img) for img in img_group]
return torch.stack(img_group, 0)
from rtfm.
Hi @marsplant,
I am also looking for a way to extract i3d features on my dataset. I don't know if you have succeeded in extracting i3d features or not? If successful can you guide me?
Thank you so much!
from rtfm.
Can you release the LoopPad part?
Thank you!
from rtfm.
Hi @marsplant, I am also looking for a way to extract i3d features on my dataset. I don't know if you have succeeded in extracting i3d features or not? If successful can you guide me? Thank you so much!
Sorry to bother you... Have ever solved the problem? If successful can you guide me?
Thank you so much!
from rtfm.
Related Issues (20)
- some questions about extracting I3D features
- xd-violence
- How to implement inference code? HOT 1
- Where do I find dir test_frame_mask, or make it? HOT 1
- how to make ground truth file and list file for shanghai tech dataset
- UCSD-Ped2 实验设置
- Custom .mat files HOT 3
- Can not reproduce the provided I3D features extracted from UCF-Crime on RTFM Github
- The UCF-Crime checkpoints link is disabled HOT 2
- Only ShanghaiTech features and checkpoint for ShanghaiTech can be used in the link
- UCF-Crime train I3d features on Google drive 下载失败—已被禁止 HOT 1
- Feature extraction results did not meet expectations
- feature extraction
- Results can't be reproduce for Sanghaitech
- Feature Extraction
- Generation of MatLab Labels
- AUC for UCF-Crime is Too low and Can't reproducible. HOT 1
- Can't download UCF_Crime test dataset
- 怎么生成ucf-i3d.list和ucf-i3d-test.list?
- checkpoints for UCF-Crime and XD-Violence datasets
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from rtfm.