Post in this thread or create a new thread in this section (Trained Models). It really is a excellent piece of software. Plus, you have to apply the mask after XSeg labeling & training, then go for SAEHD training. (or increase) denoise_dst. It really is a excellent piece of software. 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. MikeChan said: Dear all, I'm using DFL-colab 2. Everything is fast. 000 more times and the result look like great, just some masks are bad, so I tried to use XSEG. Feb 14, 2023. 2) Use “extract head” script. com XSEG Stands For : X S Entertainment GroupObtain the confidence needed to safely operate your Niton handheld XRF or LIBS analyzer. then i reccomend you start by doing some manuel xseg. 3. Video created in DeepFaceLab 2. Xseg apply/remove functions. npy","contentType":"file"},{"name":"3DFAN. Where people create machine learning projects. 0146. xseg train not working #5389. How to Pretrain Deepfake Models for DeepFaceLab. Src faceset is celebrity. Curiously, I don't see a big difference after GAN apply (0. 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. proper. Step 5: Merging. . 000 it), SAEHD pre-training (1. py","path":"models/Model_XSeg/Model. THE FILES the model files you still need to download xseg below. 7) Train SAEHD using ‘head’ face_type as regular deepfake model with DF archi. Phase II: Training. Include link to the model (avoid zips/rars) to a free file sharing of your choice (google drive, mega). Include link to the model (avoid zips/rars) to a free file sharing of your choice (google drive, mega). The problem of face recognition in lateral and lower projections. 3. , train_step_batch_size), the gradient accumulation steps (a. Reactions: frankmiller92Maybe I should give a pre-trained XSeg model a try. Just change it back to src Once you get the. I have 32 gigs of ram, and had a 40 gig page file, and still got these page file errors when starting saehd training. 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. DST and SRC face functions. Check out What does XSEG mean? along with list of similar terms on definitionmeaning. Step 2: Faces Extraction. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. During training, XSeg looks at the images and the masks you've created and warps them to determine the pixel differences in the image. oneduality • 4 yr. Basically whatever xseg images you put in the trainer will shell out. bat opened for me, from the XSEG editor to training with SAEHD (I reached 64 it, later I suspended it and continued training my model in quick96), I am with the folder "DeepFaceLab_NVIDIA_up_to_RTX2080Ti ". Also it just stopped after 5 hours. Could this be some VRAM over allocation problem? Also worth of note, CPU training works fine. Training; Blog; About; You can’t perform that action at this time. Apr 11, 2022. Contribute to idorg/DeepFaceLab by creating an account on DagsHub. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. . 训练需要绘制训练素材，就是你得用deepfacelab自带的工具，手动给图片画上遮罩。. 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. Where people create machine learning projects. Post in this thread or create a new thread in this section (Trained Models). Where people create machine learning projects. Easy Deepfake tutorial for beginners Xseg,Deepfake tutorial for beginners,deepfakes tutorial,face swap,deep fakes,d. Step 6: Final Result. I didn't try it. soklmarle; Jan 29, 2023; Replies 2 Views 597. The exciting part begins! Masked training clips training area to full_face mask or XSeg mask, thus network will train the faces properly. traceback (most recent call last) #5728 opened on Sep 24 by Ujah0. DLF installation functions. bat. Same ERROR happened on press 'b' to save XSeg model while training XSeg mask model. py","contentType":"file"},{"name. Open gili12345 opened this issue Aug 27, 2021 · 3 comments Open xseg train not working #5389. The Xseg training on src ended up being at worst 5 pixels over. Step 9 – Creating and Editing XSEG Masks (Sped Up) Step 10 – Setting Model Folder (And Inserting Pretrained XSEG Model) Step 11 – Embedding XSEG Masks into Faces Step 12 – Setting Model Folder in MVE Step 13 – Training XSEG from MVE Step 14 – Applying Trained XSEG Masks Step 15 – Importing Trained XSEG Masks to View in MVEMy joy is that after about 10 iterations, my Xseg training was pretty much done (I ran it for 2k just to catch anything I might have missed). train untill you have some good on all the faces. 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. But there is a big difference between training for 200,000 and 300,000 iterations (or XSeg training). And this trend continues for a few hours until it gets so slow that there is only 1 iteration in about 20 seconds. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. On training I make sure I enable Mask Training (If I understand this is for the Xseg Masks) Am I missing something with the pretraining? Can you please explain #3 since I'm not sure if I should or shouldn't APPLY to pretrained Xseg before I. 0 Xseg Tutorial. 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 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. Step 1: Frame Extraction. When loading XSEG on a Geforce 3080 10GB it uses ALL the VRAM. XSeg training GPU unavailable #5214. 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. py","path":"models/Model_XSeg/Model. Manually mask these with XSeg. e, a neural network that performs better, in the same amount of training time, or less. 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. Aug 7, 2022. 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. XSeg) data_src trained mask - apply the CMD returns this to me. Open 1over137 opened this issue Dec 24, 2020 · 7 comments Open XSeg training GPU unavailable #5214. 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. I solved my 6) train SAEHD issue by reducing the number of worker, I edited DeepFaceLab_NVIDIA_up_to_RTX2080ti_series _internalDeepFaceLabmodelsModel_SAEHDModel. 0 using XSeg mask training (213. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. Easy Deepfake tutorial for beginners Xseg. A pretrained model is created with a pretrain faceset consisting of thousands of images with a wide variety. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. If you want to get tips, or better understand the Extract process, then. Python Version: The one that came with a fresh DFL Download yesterday. DFL 2. . Video created in DeepFaceLab 2. The next step is to train the XSeg model so that it can create a mask based on the labels you provided. I solved my 5. However in order to get the face proportions correct, and a better likeness, the mask needs to be fit to the actual faces. 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. bat，会跳出界面绘制dst遮罩，就是框框抠抠，这是个细活儿，挺累的。 运行train. py by just changing the line 669 to. I don't see any problems with my masks in the xSeg trainer and I'm using masked training, most other settings are default. Only deleted frames with obstructions or bad XSeg. Contribute to idorg/DeepFaceLab by creating an account on DagsHub. On conversion, the settings listed in that post work best for me, but it always helps to fiddle around. Where people create machine learning projects. . k. 1. network in the training process robust to hands, glasses, and any other objects which may cover the face somehow. Train XSeg on these masks. Remove filters by clicking the text underneath the dropdowns. Contribute to idonov/DeepFaceLab by creating an account on DAGsHub. [Tooltip: Half / mid face / full face / whole face / head. Tensorflow-gpu. 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. dump ( [train_x, train_y], f) #to load it with open ("train. SRC Simpleware. You can apply Generic XSeg to src faceset. Instead of using a pretrained model. 2 is too much, you should start at lower value, use the recommended value DFL recommends (type help) and only increase if needed. Step 5: Training. gili12345 opened this issue Aug 27, 2021 · 3 comments Comments. XSeg) data_dst trained mask - apply or 5. If you include that bit of cheek, it might train as the inside of her mouth or it might stay about the same. Xseg Training is a completely different training from Regular training or Pre - Training. . Sep 15, 2022. XSeg: XSeg Mask Editing and Training How to edit, train, and apply XSeg masks. In addition to posting in this thread or the general forum. Business, Economics, and Finance. 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. pak file untill you did all the manuel xseg you wanted to do. 000. 000 iterations many masks look like. And the 2nd column and 5th column of preview photo change from clear face to yellow. XSeg in general can require large amounts of virtual memory. 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. Describe the AMP model using AMP model template from rules thread. This video takes you trough the entire process of using deepfacelab, to make a deepfake, for results in which you replace the entire head. 9794 and 0. {"payload":{"allShortcutsEnabled":false,"fileTree":{"facelib":{"items":[{"name":"2DFAN. But before you can stat training you aso have to mask your datasets, both of them, STEP 8 - XSEG MODEL TRAINING, DATASET LABELING AND MASKING: [News Thee snow apretralned Genere WF X5eg model Included wth DF (nternamodel generic xs) fyou dont have time to label aces for your own WF XSeg model or urt needto quickly pely base Wh. If you want to see how xseg is doing, stop training, apply, the open XSeg Edit. It really is a excellent piece of software. + new decoder produces subpixel clear result. After training starts, memory usage returns to normal (24/32). With XSeg you only need to mask a few but various faces from the faceset, 30-50 for regular deepfake. Where people create machine learning projects. bat compiles all the xseg faces you’ve masked. . Model first run. bat I don’t even know if this will apply without training masks. Lee - Dec 16, 2019 12:50 pm UTCForum rules. 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. Sometimes, I still have to manually mask a good 50 or more faces, depending on material. It will take about 1-2 hour. 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;. Where people create machine learning projects. PayPal Tip Jar:Lab Tutorial (basic/standard):Channel (He. Frame extraction functions. 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. It has been claimed that faces are recognized as a “whole” rather than the recognition of individual parts. After that we’ll do a deep dive into XSeg editing, training the model,…. npy","path":"facelib/2DFAN. 2. Final model config:===== Model Summary ==. The more the training progresses, the more holes in the SRC model (who has short hair) will open up where the hair disappears. This forum is for reporting errors with the Extraction process. Post_date. If it is successful, then the training preview window will open. Sometimes, I still have to manually mask a good 50 or more faces, depending on. PayPal Tip Jar:Lab:MEGA:. updated cuda and cnn and drivers. 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. Face type ( h / mf / f / wf / head ): Select the face type for XSeg training. Deepfake native resolution progress. The Xseg needs to be edited more or given more labels if I want a perfect mask. 5) Train XSeg. DeepFaceLab Model Settings Spreadsheet (SAEHD) Use the dropdown lists to filter the table. #5726 opened on Sep 9 by damiano63it. 2. Describe the SAEHD model using SAEHD model template from rules thread. The software will load all our images files and attempt to run the first iteration of our training. Dry Dock Training (Victoria, BC) Dates: September 30 - October 3, 2019 Time: 8:00am - 5:00pm Instructor: Joe Stiglich, DM Consulting Location: Camosun. 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,. SAEHD looked good after about 100-150 (batch 16), but doing GAN to touch up a bit. Post in this thread or create a new thread in this section (Trained Models) 2. 1256. 7) Train SAEHD using ‘head’ face_type as regular deepfake model with DF archi. . bat removes labeled xseg polygons from the extracted frames{"payload":{"allShortcutsEnabled":false,"fileTree":{"models/Model_XSeg":{"items":[{"name":"Model. XSeg apply takes the trained XSeg masks and exports them to the data set. DFL 2. 192 it). With the help of. Extract source video frame images to workspace/data_src. 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. Download Celebrity Facesets for DeepFaceLab deepfakes. Introduction. Where people create machine learning projects. I guess you'd need enough source without glasses for them to disappear. 5) Train XSeg. The Xseg needs to be edited more or given more labels if I want a perfect mask. XSeg allows everyone to train their model for the segmentation of a spe- Pretrained XSEG is a model for masking the generated face, very helpful to automatically and intelligently mask away obstructions. RTT V2 224: 20 million iterations of training. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. also make sure not to create a faceset. 5) Train XSeg. Requires an exact XSeg mask in both src and dst facesets. BAT script, open the drawing tool, draw the Mask of the DST. The software will load all our images files and attempt to run the first iteration of our training. XSeg-dst: uses trained XSeg model to mask using data from destination faces. 2) Use “extract head” script. Just let XSeg run a little longer instead of worrying about the order that you labeled and trained stuff. Already segmented faces can. 运行data_dst mask for XSeg trainer - edit. 05 and 0. In this video I explain what they are and how to use them. It depends on the shape, colour and size of the glasses frame, I guess. #1. With Xseg you create mask on your aligned faces, after you apply trained xseg mask, you need to train with SAEHD. First one-cycle training with batch size 64. == Model name: XSeg ==== Current iteration: 213522 ==== face_type: wf ==== p. Already segmented faces can. As you can see in the two screenshots there are problems. For DST just include the part of the face you want to replace. 0 XSeg Models and Datasets Sharing Thread. network in the training process robust to hands, glasses, and any other objects which may cover the face somehow. 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. XSegged with Groggy4 's XSeg model. 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. . Step 5. Hello, after this new updates, DFL is only worst. But usually just taking it in stride and let the pieces fall where they may is much better for your mental health. when the rightmost preview column becomes sharper stop training and run a convert. Verified Video Creator. Normally at gaming temps reach high 85-90, and its confirmed by AMD that the Ryzen 5800H is made that way. You can use pretrained model for head. This forum is for discussing tips and understanding the process involved with Training a Faceswap model. Enable random warp of samples Random warp is required to generalize facial expressions of both faces. How to share SAEHD Models: 1. added 5. Oct 25, 2020. pak” archive file for faster loading times 47:40 – Beginning training of our SAEHD model 51:00 – Color transfer. Use the 5. Thread starter thisdudethe7th; Start date Mar 27, 2021; T. If it is successful, then the training preview window will open. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. 3X to 4. 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. All images are HD and 99% without motion blur, not Xseg. Xseg editor and overlays. The dice, volumetric overlap error, relative volume difference. Instead of the trainer continuing after loading samples, it sits idle doing nothing infinitely like this:With XSeg training for example the temps stabilize at 70 for CPU and 62 for GPU. #1. learned-prd*dst: combines both masks, smaller size of both. learned-prd*dst: combines both masks, smaller size of both. I understand that SAEHD (training) can be processed on my CPU, right? Yesterday, "I tried the SAEHD method" and all the. This video was made to show the current workflow to follow when you want to create a deepfake with DeepFaceLab. Read the FAQs and search the forum before posting a new topic. bat. Where people create machine learning projects. Video created in DeepFaceLab 2. It must work if it does for others, you must be doing something wrong. S. Training XSeg is a tiny part of the entire process. 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. 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 faceDuring 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. Very soon in the Colab XSeg training process the faces at my previously SAEHD trained model (140k iterations) already look perfectly masked. Hi everyone, I'm doing this deepfake, using the head previously for me pre -trained. Fit training is a technique where you train your model on data that it wont see in the final swap then do a short "fit" train to with the actual video you're swapping out in order to get the best. As you can see the output show the ERROR that was result in a double 'XSeg_' in path of XSeg_256_opt. For those wanting to become Certified CPTED Practitioners the process will involve the following steps: 1. The only available options are the three colors and the two "black and white" displays. Consol logs. 5. Even though that. Setting Value Notes; iterations: 100000: Or until previews are sharp with eyes and teeth details. k. I have now moved DFL to the Boot partition, the behavior remains the same. XSeg) data_dst/data_src mask for XSeg trainer - remove. - Issues · nagadit/DeepFaceLab_Linux. Double-click the file labeled ‘6) train Quick96. . Copy link. Include link to the model (avoid zips/rars) to a free file. Intel i7-6700K (4GHz) 32GB RAM (Already increased pagefile on SSD to 60 GB) 64 bit. a. Actual behavior. Src faceset should be xseg'ed and applied. The software will load all our images files and attempt to run the first iteration of our training. 2) extract images from video data_src. A skill in programs such as AfterEffects or Davinci Resolve is also desirable. tried on studio drivers and gameready ones. Increased page file to 60 gigs, and it started. 000 it). Contribute to idonov/DeepFaceLab by creating an account on DagsHub. I have to lower the batch_size to 2, to have it even start. 3) Gather rich src headset from only one scene (same color and haircut) 4) Mask whole head for src and dst using XSeg editor. This video takes you trough the entire process of using deepfacelab, to make a deepfake, for results in which you replace the entire head. Model training fails. It might seem high for CPU, but considering it wont start throttling before getting closer to 100 degrees, it's fine. 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 faceDuring 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. I've posted the result in a video. BAT script, open the drawing tool, draw the Mask of the DST. 7) Train SAEHD using ‘head’ face_type as regular deepfake model with DF archi. Looking for the definition of XSEG? Find out what is the full meaning of XSEG on Abbreviations. Container for all video, image, and model files used in the deepfake project. #DeepFaceLab #ModelTraning #Iterations #Resolution256 #Colab #WholeFace #Xseg #wf_XSegAs I don't know what the pictures are, I cannot be sure. prof. Its a method of randomly warping the image as it trains so it is better at generalization. During training, XSeg looks at the images and the masks you've created and warps them to determine the pixel differences in the image. 3: XSeg Mask Labeling & XSeg Model Training Q1: XSeg is not mandatory because the faces have a default mask. Contribute to idonov/DeepFaceLab by creating an account on DagsHub. XSeg) data_src trained mask - apply. bat. Where people create machine learning projects. XSeg-prd: uses. added 5. Enter a name of a new model : new Model first run. 000 it) and SAEHD training (only 80. In the XSeg viewer there is a mask on all faces. Extra trained by Rumateus. XSeg-prd: uses trained XSeg model to mask using data from source faces. Get any video, extract frames as jpg and extract faces as whole face, don't change any names, folders, keep everything in one place, make sure you don't have any long paths or weird symbols in the path names and try it again. py","contentType":"file"},{"name. For a 8gb card you can place on. Use the 5. I used to run XSEG on a Geforce 1060 6GB and it would run fine at batch 8. 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. Grab 10-20 alignments from each dst/src you have, while ensuring they vary and try not to go higher than ~150 at first. Mark your own mask only for 30-50 faces of dst video. py","path":"models/Model_XSeg/Model. Notes, tests, experience, tools, study and explanations of the source code. Please mark. bat scripts to enter the training phase, and the face parameters use WF or F, and BS use the default value as needed. 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. Describe the XSeg model using XSeg model template from rules thread. Problems Relative to installation of "DeepFaceLab". I have a model with quality 192 pretrained with 750. 3. Enjoy it. py","contentType":"file"},{"name. py","contentType":"file"},{"name. xseg) Data_Dst Mask for Xseg Trainer - Edit. Increased page file to 60 gigs, and it started. It will take about 1-2 hour. 18K subscribers in the SFWdeepfakes community. py","contentType":"file"},{"name. Part 1. . I do recommend che. thisdudethe7th Guest. remember that your source videos will have the biggest effect on the outcome!Out of curiosity I saw you're using xseg - did you watch xseg train, and then when you see a spot like those shiny spots begin to form, stop training and go find several frames that are like the one with spots, mask them, rerun xseg and watch to see if the problem goes away, then if it doesn't mask more frames where the shiniest faces. 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. The images in question are the bottom right and the image two above that. In a paper published in the Quarterly Journal of Experimental. Download Megan Fox Faceset - Face: F / Res: 512 / XSeg: Generic / Qty: 3,726Contribute to idonov/DeepFaceLab by creating an account on DagsHub. It is now time to begin training our deepfake model. Step 4: Training. then copy pastE those to your xseg folder for future training.