Share. 2 使用Xseg模型（推荐） 38:03 – Manually Xseg masking Jim/Ernest 41:43 – Results of training after manual Xseg’ing was added to Generically trained mask 43:03 – Applying Xseg training to SRC 43:45 – Archiving our SRC faces into a “faceset. Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Business, Economics, and Finance. 3. XSeg allows everyone to train their model for the segmentation of a spe-Jan 11, 2021. Post in this thread or create a new thread in this section (Trained Models) 2. #DeepFaceLab #ModelTraning #Iterations #Resolution256 #Colab #WholeFace #Xseg #wf_XSegAs I don't know what the pictures are, I cannot be sure. Then I'll apply mask, edit material to fix up any learning issues, and I'll continue training without the xseg facepak from then on. Link to that. pak file untill you did all the manuel xseg you wanted to do. tried on studio drivers and gameready ones. Already segmented faces can. Setting Value Notes; iterations: 100000: Or until previews are sharp with eyes and teeth details. I was less zealous when it came to dst, because it was longer and I didn't really understand the flow/missed some parts in the guide. Include link to the model (avoid zips/rars) to a free file sharing of your choice (google drive, mega). I've posted the result in a video. Differences from SAE: + new encoder produces more stable face and less scale jitter. PayPal Tip Jar:Lab Tutorial (basic/standard):Channel (He. During training, XSeg looks at the images and the masks you've created and warps them to determine the pixel differences in the image. During training check previews often, if some faces have bad masks after about 50k iterations (bad shape, holes, blurry), save and stop training, apply masks to your dataset, run editor, find faces with bad masks by enabling XSeg mask overlay in the editor, label them and hit esc to save and exit and then resume XSeg model training, when. XSeg) train. This is fairly expected behavior to make training more robust, unless it is incorrectly masking your faces after it has been trained and applied to merged faces. Do you see this issue without 3D parallelism? According to the documentation, train_batch_size is aggregated by the batch size that a single GPU processes in one forward/backward pass (a. . . Without manually editing masks of a bunch of pics, but just adding downloaded masked pics to the dst aligned folder for xseg training, I'm wondering how DFL learns to. learned-dst: uses masks learned during training. Training; Blog; About;Then I'll apply mask, edit material to fix up any learning issues, and I'll continue training without the xseg facepak from then on. I was less zealous when it came to dst, because it was longer and I didn't really understand the flow/missed some parts in the guide. I've downloaded @Groggy4 trained Xseg model and put the content on my model folder. How to Pretrain Deepfake Models for DeepFaceLab. From the project directory, run 6. XSeg) data_dst/data_src mask for XSeg trainer - remove. 9794 and 0. Deepfake native resolution progress. You can then see the trained XSeg mask for each frame, and add manual masks where needed. . Model training is consumed, if prompts OOM. DeepFaceLab is an open-source deepfake system created by iperov for face swapping with more than 3,000 forks and 13,000 stars in Github: it provides an imperative and easy-to-use pipeline for people to use with no comprehensive understanding of deep learning framework or with model implementation required, while remains a flexible and loose coupling. #1. Frame extraction functions. e, a neural network that performs better, in the same amount of training time, or less. With a batch size 512, the training is nearly 4x faster compared to the batch size 64! Moreover, even though the batch size 512 took fewer steps, in the end it has better training loss and slightly worse validation loss. For this basic deepfake, we’ll use the Quick96 model since it has better support for low-end GPUs and is generally more beginner friendly. Src faceset should be xseg'ed and applied. It learns this to be able to. This video takes you trough the entire process of using deepfacelab, to make a deepfake, for results in which you replace the entire head. Must be diverse enough in yaw, light and shadow conditions. #1. XSeg) data_src trained mask - apply. bat’. == Model name: XSeg ==== Current iteration: 213522 ==== face_type: wf ==== p. network in the training process robust to hands, glasses, and any other objects which may cover the face somehow. . 0 How to make XGBoost model to learn its mistakes. Include link to the model (avoid zips/rars) to a free file sharing of your choice (google drive, mega) In addition to posting in this thread or. Reactions: frankmiller92Maybe I should give a pre-trained XSeg model a try. DeepFaceLab Model Settings Spreadsheet (SAEHD) Use the dropdown lists to filter the table. By modifying the deep network architectures [[2], [3], [4]] or designing novel loss functions [[5], [6], [7]] and training strategies, a model can learn highly discriminative facial features for face. resolution: 128: Increasing resolution requires significant VRAM increase: face_type: f: learn_mask: y: optimizer_mode: 2 or 3: Modes 2/3 place work on the gpu and system memory. With XSeg you only need to mask a few but various faces from the faceset, 30-50 for regular deepfake. Easy Deepfake tutorial for beginners Xseg. python xgboost continue training on existing model. 2. py","contentType":"file"},{"name. It might seem high for CPU, but considering it wont start throttling before getting closer to 100 degrees, it's fine. I have an Issue with Xseg training. In this DeepFaceLab XSeg tutorial I show you how to make better deepfakes and take your composition to the next level! I’ll go over what XSeg is and some. When the face is clear enough, you don't need to do manual masking, you can apply Generic XSeg and get. Could this be some VRAM over allocation problem? Also worth of note, CPU training works fine. Src faceset is celebrity. Enjoy it. But there is a big difference between training for 200,000 and 300,000 iterations (or XSeg training). Just change it back to src Once you get the. SRC Simpleware. 000 it). This forum has 3 topics, 4 replies, and was last updated 3 months, 1 week ago by. However, when I'm merging, around 40 % of the frames "do not have a face". XSeg Model Training. Training XSeg is a tiny part of the entire process. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. Change: 5. Consol logs. 0 XSeg Models and Datasets Sharing Thread. Already segmented faces can. Contribute to idorg/DeepFaceLab by creating an account on DagsHub. 023 at 170k iterations, but when I go to the editor and look at the mask, none of those faces have a hole where I have placed a exclusion polygon around. 1) clear workspace. Again, we will use the default settings. 4 cases both for the SAEHD and Xseg, and with enough and not enough pagefile: SAEHD with Enough Pagefile:The DFL and FaceSwap developers have not been idle, for sure: it’s now possible to use larger input images for training deepfake models (see image below), though this requires more expensive video cards; masking out occlusions (such as hands in front of faces) in deepfakes has been semi-automated by innovations such as XSEG training;. Pass the in. 建议萌. caro_kann; Dec 24, 2021; Replies 6 Views 3K. pkl", "w") as f: pkl. And the 2nd column and 5th column of preview photo change from clear face to yellow. bat I don’t even know if this will apply without training masks. If your model is collapsed, you can only revert to a backup. XSeg: XSeg Mask Editing and Training How to edit, train, and apply XSeg masks. For DST just include the part of the face you want to replace. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. In this DeepFaceLab XSeg tutorial I show you how to make better deepfakes and take your composition to the next level! I’ll go over what XSeg is and some important terminology, then we’ll use the generic mask to shortcut the entire process. 5. . Where people create machine learning projects. Where people create machine learning projects. 1. Mar 27, 2021 #1 (account deleted) Groggy4 NotSure. Increased page file to 60 gigs, and it started. {"payload":{"allShortcutsEnabled":false,"fileTree":{"facelib":{"items":[{"name":"2DFAN. network in the training process robust to hands, glasses, and any other objects which may cover the face somehow. Use the 5. Copy link. bat’. XSeg in general can require large amounts of virtual memory. XSeg: XSeg Mask Editing and Training How to edit, train, and apply XSeg masks. Open 1over137 opened this issue Dec 24, 2020 · 7 comments Open XSeg training GPU unavailable #5214. Describe the XSeg model using XSeg model template from rules thread. Model training is consumed, if prompts OOM. 1) except for some scenes where artefacts disappear. 00:00 Start00:21 What is pretraining?00:50 Why use i. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. Manually fix any that are not masked properly and then add those to the training set. 3: XSeg Mask Labeling & XSeg Model Training Q1: XSeg is not mandatory because the faces have a default mask. 0 to train my SAEHD 256 for over one month. Again, we will use the default settings. Choose one or several GPU idxs (separated by comma). I've been trying to use Xseg for the first time, today, and everything looks "good", but after a little training, I'm going back to the editor to patch/remask some pictures, and I can't see the mask overlay. XSeg) data_dst trained mask - apply or 5. 5. Increased page file to 60 gigs, and it started. XSeg 蒙版还将帮助模型确定面部尺寸和特征，从而产生更逼真的眼睛和嘴巴运动。虽然默认蒙版可能对较小的面部类型有用，但较大的面部类型（例如全脸和头部）需要自定义 XSeg 蒙版才能获得. I'm not sure if you can turn off random warping for XSeg training and frankly I don't thing you should, it helps to make the mask training be able to generalize on new data sets. 18K subscribers in the SFWdeepfakes community. bat scripts to enter the training phase, and the face parameters use WF or F, and BS use the default value as needed. The more the training progresses, the more holes in the SRC model (who has short hair) will open up where the hair disappears. It should be able to use GPU for training. In my own tests, I only have to mask 20 - 50 unique frames and the XSeg Training will do the rest of the job for you. Its a method of randomly warping the image as it trains so it is better at generalization. ProTip! Adding no:label will show everything without a label. First one-cycle training with batch size 64. 1over137 opened this issue Dec 24, 2020 · 7 comments Comments. Describe the SAEHD model using SAEHD model template from rules thread. Actual behavior XSeg trainer looks like this: (This is from the default Elon Musk video by the way) Steps to reproduce I deleted the labels, then labeled again. I don't see any problems with my masks in the xSeg trainer and I'm using masked training, most other settings are default. Include link to the model (avoid zips/rars) to a free file sharing of your choice (google drive, mega). 0 XSeg Models and Datasets Sharing Thread. Where people create machine learning projects. proper. XSeg) train issue by. 这一步工作量巨大，要给每一个关键动作都画上遮罩，作为训练数据，数量大约在几十到几百张不等。. Verified Video Creator. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. The images in question are the bottom right and the image two above that. Intel i7-6700K (4GHz) 32GB RAM (Already increased pagefile on SSD to 60 GB) 64 bit. 2. I have 32 gigs of ram, and had a 40 gig page file, and still got these page file errors when starting saehd training. 3. It works perfectly fine when i start Training with Xseg but after a few minutes it stops for a few seconds and then continues but slower. In the XSeg viewer there is a mask on all faces. Part 2 - This part has some less defined photos, but it's. Where people create machine learning projects. Does Xseg training affects the regular model training? eg. Doing a rough project, I’ve run generic XSeg, going through the frames in edit on the destination, several frames have picked up the background as part of the face, may be a silly question, but if I manually add the mask boundary in edit view do I have to do anything else to apply the new mask area or will that not work, it. 2 is too much, you should start at lower value, use the recommended value DFL recommends (type help) and only increase if needed. It is used at 2 places. Double-click the file labeled ‘6) train Quick96. Make a GAN folder: MODEL/GAN. Step 2: Faces Extraction. #5726 opened on Sep 9 by damiano63it. All images are HD and 99% without motion blur, not Xseg. Extra trained by Rumateus. HEAD masks are not ideal since they cover hair, neck, ears (depending on how you mask it but in most cases with short haired males faces you do hair and ears) which aren't fully covered by WF and not at all by FF,. During training check previews often, if some faces have bad masks after about 50k iterations (bad shape, holes, blurry), save and stop training, apply masks to your dataset, run editor, find faces with bad masks by enabling XSeg mask overlay in the editor, label them and hit esc to save and exit and then resume XSeg model training, when. learned-prd+dst: combines both masks, bigger size of both. As I understand it, if you had a super-trained model (they say its 400-500 thousand iterations) for all face positions, then you wouldn’t have to start training every time. 7) Train SAEHD using ‘head’ face_type as regular deepfake model with DF archi. DFL 2. Download this and put it into the model folder. This video takes you trough the entire process of using deepfacelab, to make a deepfake, for results in which you replace the entire head. py","path":"models/Model_XSeg/Model. Download Megan Fox Faceset - Face: F / Res: 512 / XSeg: Generic / Qty: 3,726Contribute to idonov/DeepFaceLab by creating an account on DagsHub. Blurs nearby area outside of applied face mask of training samples. Also it just stopped after 5 hours. Mark your own mask only for 30-50 faces of dst video. in xseg model the exclusions indeed are learned and fine, the issue new is in training preview, it doesn't show that , i haven't done yet, so now sure if its a preview bug what i have done so far: - re checked frames to see if. With Xseg you create mask on your aligned faces, after you apply trained xseg mask, you need to train with SAEHD. When the face is clear enough, you don't need. Download RTT V2 224;Same problem here when I try an XSeg train, with my rtx2080Ti (using the rtx2080Ti build released on the 01-04-2021, same issue with end-december builds, work only with the 12-12-2020 build). Where people create machine learning projects. cpu_count = multiprocessing. 000 it), SAEHD pre-training (1. 2. 3. In my own tests, I only have to mask 20 - 50 unique frames and the XSeg Training will do the rest of the job for you. 2) extract images from video data_src. 1. Download Celebrity Facesets for DeepFaceLab deepfakes. I often get collapses if I turn on style power options too soon, or use too high of a value. I have now moved DFL to the Boot partition, the behavior remains the same. xseg) Train. added 5. Double-click the file labeled ‘6) train Quick96. I didn't filter out blurry frames or anything like that because I'm too lazy so you may need to do that yourself. xseg) Train. S. I turn random color transfer on for the first 10-20k iterations and then off for the rest. In this DeepFaceLab XSeg tutorial I show you how to make better deepfakes and take your composition to the next level! I’ll go over what XSeg is and some important terminology,. DST and SRC face functions. [new] No saved models found. In addition to posting in this thread or the general forum. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. I've been trying to use Xseg for the first time, today, and everything looks "good", but after a little training, I'm going back to the editor to patch/remask some pictures, and I can't see the mask. SRC Simpleware. After training starts, memory usage returns to normal (24/32). This video was made to show the current workflow to follow when you want to create a deepfake with DeepFaceLab. To conclude, and answer your question, a smaller mini-batch size (not too small) usually leads not only to a smaller number of iterations of a training algorithm, than a large batch size, but also to a higher accuracy overall, i. But usually just taking it in stride and let the pieces fall where they may is much better for your mental health. Enable random warp of samples Random warp is required to generalize facial expressions of both faces. Post processing. If I train src xseg and dst xseg separately, vs training a single xseg model for both src and dst? Does this impact the quality in any way? 2. I could have literally started merging after about 3-4 hours (on a somewhat slower AMD integrated GPU). py","contentType":"file"},{"name. XSeg-prd: uses. on a 320 resolution it takes upto 13-19 seconds . Consol logs. Deep convolutional neural networks (DCNNs) have made great progress in recognizing face images under unconstrained environments [1]. I just continue training for brief periods, applying new mask, then checking and fixing masked faces that need a little help. py","path":"models/Model_XSeg/Model. Step 6: Final Result. 3X to 4. {"payload":{"allShortcutsEnabled":false,"fileTree":{"models/Model_XSeg":{"items":[{"name":"Model. Keep shape of source faces. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. Step 3: XSeg Masks. You can see one of my friend in Princess Leia ;-) I've put same scenes with different. 3. Normally at gaming temps reach high 85-90, and its confirmed by AMD that the Ryzen 5800H is made that way. Thread starter thisdudethe7th; Start date Mar 27, 2021; T. Requires an exact XSeg mask in both src and dst facesets. DFL 2. Several thermal modes to choose from. Xseg editor and overlays. 1 Dump XGBoost model with feature map using XGBClassifier. , train_step_batch_size), the gradient accumulation steps (a. In addition to posting in this thread or the general forum. Contribute to idorg/DeepFaceLab by creating an account on DagsHub. soklmarle; Jan 29, 2023; Replies 2 Views 597. Include link to the model (avoid zips/rars) to a free file sharing of your choice (google drive, mega). Just let XSeg run a little longer. Also it just stopped after 5 hours. train untill you have some good on all the faces. xseg) Data_Dst Mask for Xseg Trainer - Edit. 0 using XSeg mask training (100. I don't see any problems with my masks in the xSeg trainer and I'm using masked training, most other settings are default. Describe the XSeg model using XSeg model template from rules thread. You could also train two src files together just rename one of them to dst and train. #5727 opened on Sep 19 by WagnerFighter. SAEHD is a new heavyweight model for high-end cards to achieve maximum possible deepfake quality in 2020. Timothy B. After training starts, memory usage returns to normal (24/32). dump ( [train_x, train_y], f) #to load it with open ("train. If you include that bit of cheek, it might train as the inside of her mouth or it might stay about the same. slow We can't buy new PC, and new cards, after you every new updates ))). It is now time to begin training our deepfake model. Then if we look at the second training cycle losses for each batch size : Leave both random warp and flip on the entire time while training face_style_power 0 We'll increase this later You want only the start of training to have styles on (about 10-20k interations then set both to 0), usually face style 10 to morph src to dst, and/or background style 10 to fit the background and dst face border better to the src face. I have 32 gigs of ram, and had a 40 gig page file, and still got these page file errors when starting saehd training. At last after a lot of training, you can merge. 1 participant. Notes; Sources: Still Images, Interviews, Gunpowder Milkshake, Jett, The Haunting of Hill House. Train the fake with SAEHD and whole_face type. Requesting Any Facial Xseg Data/Models Be Shared Here. It will take about 1-2 hour. In a paper published in the Quarterly Journal of Experimental. With the help of. bat removes labeled xseg polygons from the extracted frames{"payload":{"allShortcutsEnabled":false,"fileTree":{"models/Model_XSeg":{"items":[{"name":"Model. After that we’ll do a deep dive into XSeg editing, training the model,…. added XSeg model. XSeg-dst: uses trained XSeg model to mask using data from destination faces. If it is successful, then the training preview window will open. Lee - Dec 16, 2019 12:50 pm UTCForum rules. 5) Train XSeg. All you need to do is pop it in your model folder along with the other model files, use the option to apply the XSEG to the dst set, and as you train you will see the src face learn and adapt to the DST's mask. I realized I might have incorrectly removed some of the undesirable frames from the dst aligned folder before I started training, I just deleted them to the. Plus, you have to apply the mask after XSeg labeling & training, then go for SAEHD training. However in order to get the face proportions correct, and a better likeness, the mask needs to be fit to the actual faces. 训练Xseg模型. I used to run XSEG on a Geforce 1060 6GB and it would run fine at batch 8. when the rightmost preview column becomes sharper stop training and run a convert. Where people create machine learning projects. Include link to the model (avoid zips/rars) to a free file sharing of your choice (google drive, mega) In addition to posting in this thread or. Actual behavior. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. Choose the same as your deepfake model. It has been claimed that faces are recognized as a “whole” rather than the recognition of individual parts. bat训练遮罩，设置脸型和batch_size，训练个几十上百万，回车结束。 XSeg遮罩训练素材是不区分是src和dst。 2. The Xseg needs to be edited more or given more labels if I want a perfect mask. Hello, after this new updates, DFL is only worst. 2) Use “extract head” script. Could this be some VRAM over allocation problem? Also worth of note, CPU training works fine. [Tooltip: Half / mid face / full face / whole face / head. #1. Read all instructions before training. XSeg is just for masking, that's it, if you applied it to SRC and all masks are fine on SRC faces, you don't touch it anymore, all SRC faces are masked, you then did the same for DST (labeled, trained xseg, applied), now this DST is masked properly, if new DST looks overall similar (same lighting, similar angles) you probably won't need to add. 2. Please mark. . DF Vagrant. X. When loading XSEG on a Geforce 3080 10GB it uses ALL the VRAM. then copy pastE those to your xseg folder for future training. 4 cases both for the SAEHD and Xseg, and with enough and not enough pagefile: SAEHD with Enough Pagefile:The DFL and FaceSwap developers have not been idle, for sure: it’s now possible to use larger input images for training deepfake models (see image below), though this requires more expensive video cards; masking out occlusions (such as hands in front of faces) in deepfakes has been semi-automated by innovations such as XSEG training;. + pixel loss and dssim loss are merged together to achieve both training speed and pixel trueness. Post in this thread or create a new thread in this section (Trained Models). 000 it) and SAEHD training (only 80. Double-click the file labeled ‘6) train Quick96. first aply xseg to the model. a. All reactions1. xseg) Data_Dst Mask for Xseg Trainer - Edit. 000 it), SAEHD pre-training (1. Training XSeg is a tiny part of the entire process. . Remove filters by clicking the text underneath the dropdowns. Sydney Sweeney, HD, 18k images, 512x512. 3. It really is a excellent piece of software. Aug 7, 2022. Where people create machine learning projects. During training check previews often, if some faces have bad masks after about 50k iterations (bad shape, holes, blurry), save and stop training, apply masks to your dataset, run editor, find faces with bad masks by enabling XSeg mask overlay in the editor, label them and hit esc to save and exit and then resume XSeg model training, when. 16 XGBoost produce prediction result and probability. thisdudethe7th Guest. 1. k. . after that just use the command. This video was made to show the current workflow to follow when you want to create a deepfake with DeepFaceLab. The Xseg training on src ended up being at worst 5 pixels over. Looking for the definition of XSEG? Find out what is the full meaning of XSEG on Abbreviations. pkl", "r") as f: train_x, train_y = pkl. Describe the AMP model using AMP model template from rules thread. . npy","contentType":"file"},{"name":"3DFAN. Pretrained XSEG is a model for masking the generated face, very helpful to automatically and intelligently mask away obstructions. XSeg) train. DeepFaceLab is the leading software for creating deepfakes. bat. Hi all, very new to DFL -- I tried to use the exclusion polygon tool on dst source mouth in xseg editor. 5. if some faces have wrong or glitchy mask, then repeat steps: split run edit find these glitchy faces and mask them merge train further or restart training from scratch Restart training of XSeg model is only possible by deleting all 'model\XSeg_*' files. npy","path. However, since some state-of-the-art face segmentation models fail to generate fine-grained masks in some partic-ular shots, the XSeg was introduced in DFL. Manually labeling/fixing frames and training the face model takes the bulk of the time. For a 8gb card you can place on. Extract source video frame images to workspace/data_src. Video created in DeepFaceLab 2. learned-prd*dst: combines both masks, smaller size of both. this happend on both Xsrg and SAEHD training, during initializing phase after loadind in the sample, the prpgram erros and stops memory usege start climbing while loading the Xseg mask applyed facesets. I have 32 gigs of ram, and had a 40 gig page file, and still got these page file errors when starting saehd. For those wanting to become Certified CPTED Practitioners the process will involve the following steps: 1. Very soon in the Colab XSeg training process the faces at my previously SAEHD trained model (140k iterations) already look perfectly masked. ago. 000 iterations, I disable the training and trained the model with the final dst and src 100. The problem of face recognition in lateral and lower projections. First one-cycle training with batch size 64. SAEHD Training Failure · Issue #55 · chervonij/DFL-Colab · GitHub. Manually mask these with XSeg. A skill in programs such as AfterEffects or Davinci Resolve is also desirable. Copy link 1over137 commented Dec 24, 2020. bat removes labeled xseg polygons from the extracted frames{"payload":{"allShortcutsEnabled":false,"fileTree":{"models/Model_XSeg":{"items":[{"name":"Model. During training check previews often, if some faces have bad masks after about 50k iterations (bad shape, holes, blurry), save and stop training, apply masks to your dataset, run editor, find faces with bad masks by enabling XSeg mask overlay in the editor, label them and hit esc to save and exit and then resume XSeg model training, when. Oct 25, 2020. Quick96 seems to be something you want to use if you're just trying to do a quick and dirty job for a proof of concept or if it's not important that the quality is top notch. Final model config:===== Model Summary ==. you’ll have to reduce number of dims (in SAE settings) for your gpu (probably not powerful enough for the default values) train for 12 hrs and keep an eye on the preview and loss numbers. Open gili12345 opened this issue Aug 27, 2021 · 3 comments Open xseg train not working #5389. #4. Running trainer. Actual behavior XSeg trainer looks like this: (This is from the default Elon Musk video by the way) Steps to reproduce I deleted the labels, then labeled again. Xseg training functions.