Comments (4)
Hi @davidzhangyuanhan ,
thanks for your sharing research to the community.
could you share more the parameter you use during training or any undescribed in the paper?
however, the training results i tried is still cant compared to the result in your paper.
as for now, i found still so many False Positives.
Thanks
from celeba-spoof.
@davidzhangyuanhan I'd appreciate any feedback on this.
from celeba-spoof.
Because of the rule of the company, I can't share the training script recently. But I can explain any training details here if you ask.
from celeba-spoof.
Here, we share part of our data loading pipeline code:
%%%%Transform%%%%%
self.transform_ColorJitter= transforms.Compose([
transforms.Resize((self.new_width, self.new_height)),
transforms.ColorJitter(saturation = 1),
transforms.ToTensor(),
transforms.Normalize(mean = (0.5, 0.5, 0.5), std = (0.5, 0.5, 0.5))
])
def __getitem__(self, idx):
filename = self.metas[idx][0]
cls = self.metas[idx][1]
img = cv2_loader(filename)
real_h,real_w,c = img.shape
#Load bounding box
assert os.path.exists(filename[:-4] + '_BB.txt'),'path not exists' + filename
with open(filename[:-4] + '_BB.txt','r') as f:
material = f.readline()
try:
x,y,w,h,score = material.strip().split(' ')
except:
print('[Rank' + str(self.rank) + ']' + filename)
try:
w = int(float(w))
h = int(float(h))
x = int(float(x))
y = int(float(y))
w = int(w*(real_w / 224))
h = int(h*(real_h / 224))
x = int(x*(real_w / 224))
y = int(y*(real_h / 224))
#Crop image
if y < 0:
y1 = 0
else:
y1 = y
if x < 0:
x1 = 0
else:
x1 = x
if y1 + h > real_h:
y2 = real_h
else:
y2 = y + h
if x1 + w > real_w:
x2 = real_w
else:
x2 = x + w
img = img[y1:y2,x1:x2,:]
assert img.shape[0] != 0 and img.shape[1] != 0,'img_path:' + filename + ' idx:' + str(idx)
img = Image.fromarray(cv2.cvtColor(img,cv2.COLOR_BGR2RGB))
img = self.transform_ColorJitter(img)
assert img.shape[0] == 3,filename
return img, cls
from celeba-spoof.
Related Issues (20)
- 关于比赛测试指标的疑问?
- Is it possible to run the code in run-time? HOT 2
- Dataloader/Data-loading pipeline HOT 1
- 关于predict输出 HOT 2
- Is it possible to use the pre-trained weight commercially? HOT 1
- Dataset quality HOT 11
- Question about validation data? HOT 1
- Prediction
- about dataloader HOT 1
- 训练时深度图如何处理 HOT 7
- To be deleted
- Downloading and preparing dataset using command-line
- empty bounding box file HOT 2
- AttributeError: 'NoneType' object has no attribute 'shape' HOT 5
- AEnet results on CASIA-MFSD. HOT 1
- image annotation HOT 1
- AENet results on CASIA-MFSD HOT 8
- How to download Siw HOT 3
- output changes after each predict
- Download dataset images HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from celeba-spoof.