***100% ai generated***
I'm really liking these outputs from Krea2. As i keep experimenting and using it, it's growing on me. Some facial variance is expected, obviously as identity LoRA's efficacy is around 82-88%. Considering all the other parameters, Custom face generation has certainly taken a new leap, that's for sure.
----------------------------------
Custom face generations available
***100% ai generated***
I'm really liking these outputs from Krea2. As i keep experimenting and using it, it's growing on me. Some facial variance is expected, obviously as identity LoRA's efficacy is around 82-88%. Considering all the other parameters, Custom face generation has certainly taken a new leap, that's for sure.
----------------------------------
Custom face generations available
***100% ai generated***
I'm really liking these outputs from Krea2. As i keep experimenting and using it, it's growing on me. Some facial variance is expected, obviously as identity LoRA's efficacy is around 82-88%. Considering all the other parameters, Custom face generation has certainly taken a new leap, that's for sure.
----------------------------------
Custom face generations available
***100% ai generated***
I'm really liking these outputs from Krea2. As i keep experimenting and using it, it's growing on me. Some facial variance is expected, obviously as identity LoRA's efficacy is around 82-88%. Considering all the other parameters, Custom face generation has certainly taken a new leap, that's for sure.
----------------------------------
Custom face generations available
***100% ai generated***
I really liked the face of one of my model bhabhi. Hence, i tried to maintain the same face across different scenarios just to see if the facial identity holds up. Even for initial runs the consistency and facial mapping looks good.
For testing, I even included the rose tattoo on the shoulder to keep the body features under the scanner. Turned out pretty good.
---------------------------------
Custom Requests available
***100% ai generated***
I really liked the face of one of my model bhabhi. Hence, i tried to maintain the same face across different scenarios just to see if the facial identity holds up. Even for initial runs the consistency and facial mapping looks good.
For testing, I even included the rose tattoo on the shoulder to keep the body features under the scanner. Turned out pretty good.
---------------------------------
Custom Requests available
***100% ai generated***
I really liked the face of one of my model bhabhi. Hence, i tried to maintain the same face across different scenarios just to see if the facial identity holds up. Even for initial runs the consistency and facial mapping looks good.
For testing, I even included the rose tattoo on the shoulder to keep the body features under the scanner. Turned out pretty good.
---------------------------------
Custom Requests available
100% ai generated
I really liked the face of one of my model bhabhi. Hence, i tried to maintain the same face across different scenarios just to see if the facial identity holds up. Even for initial runs the consistency and facial mapping looks good.
For testing, I even included the rose tattoo on the shoulder to keep the body features under the scanner. Turned out pretty good.
Custom Requests available
***100% ai generated***
I really liked the face of one of my model bhabhi. Hence, i tried to maintain the same face across different scenarios just to see if the facial identity holds up. Even for initial runs the consistency and facial mapping looks good.
For testing, I even included the rose tattoo on the shoulder to keep the body features under the scanner. Turned out pretty good
I thought of doing some targeted likeness transfer of my AI creations.
I happened to like the face of one model, but the body of another. Flux is really handy in this regard.
I'm happy with the results as i possibly can be.
I thought of doing some targeted likeness transfer of my AI creations.
I happened to like the face of one model, but the body of another. Flux is really handy in this regard.
I'm happy with the results as i possibly can be.
Recently, post grok ban and censorship, i have been playing with open source models (both image and videos). I use runpod instances, with my personal custom, and fine tuned workflows.
Flux i believe, is still the king. Krea 2, is catching up, Qwen is good for specific, pinpoint edits. Of course, one must know how to write exact required prompts.
In my experience, reusable prompts are okish, to a certain degree but for a specific edit, to match facial expression, jewellery, pose etc. requires finesse, hence one must know how to alter prompts according to the given image.
Anyways, the post is about results i got from Flux, Krea, Qwen, etc. I used a real photo of a model and tried to merge it with a picture of a 100% ai generated face, i created using Grok. I am still thinking about results. I think the sharper the reference image, more realistic and accurate is the result.
I am deliberately not mentioning, which result is from which open-source dataset. To test the waters. Pls tell me what result do you prefer. What seems more realistic ? 1, 2, or 3 ?
Recently, post grok ban and censorship, i have been playing with open source models (both image and videos). I use runpod instances, with my personal custom, and fine tuned workflows.
Flux i believe, is still the king. Krea 2, is catching up, Qwen is good for specific, pinpoint edits. Of course, one must know how to write exact required prompts.
In my experience, reusable prompts are okish, to a certain degree but for a specific edit, to match facial expression, jewellery, pose etc. requires finesse, hence one must know how to alter prompts according to the given image.
Anyways, the post is about results i got from Flux, Krea, Qwen, etc. I used a real photo of a model and tried to merge it with a picture of a 100% ai generated face, i created using Grok. I am still thinking about results. I think the sharper the reference image, more realistic and accurate is the result.
I am deliberately not mentioning, which result is from which open-source dataset. To test the waters. Pls tell me what result do you prefer. What seems more realistic ? 1, 2, or 3 ?
Recently, post grok ban and censorship, i have been playing with open source models (both image and videos). I use runpod instances, with my personal custom, and fine tuned workflows.
Flux i believe, is still the king. Krea 2, is catching up, Qwen is good for specific, pinpoint edits. Of course, one must know how to write exact required prompts.
In my experience, reusable prompts are okish, to a certain degree but for a specific edit, to match facial expression, jewellery, pose etc. requires finesse, hence one must know how to alter prompts according to the given image.
Anyways, the post is about results i got from Flux, Krea, Qwen, etc. I used a real photo of a model and tried to merge it with a picture of a 100% ai generated face, i created using Grok. I am still thinking about results. I think the sharper the reference image, more realistic and accurate is the result.
I am deliberately not mentioning, which result is from which open-source dataset. To test the waters. Pls tell me what result do you prefer. What seems more realistic ? 1, 2, or 3 ?
Recently, post grok ban and censorship, i have been playing with open source models (both image and videos). I use runpod instances, with my personal custom, and fine tuned workflows.
Flux i believe, is still the king. Krea 2, is catching up, Qwen is good for specific, pinpoint edits. Of course, one must know how to write exact required prompts.
In my experience, reusable prompts are okish, to a certain degree but for a specific edit, to match facial expression, jewellery, pose etc. requires finesse, hence one must know how to alter prompts according to the given image.
Anyways, the post is about results i got from Flux, Krea, Qwen, etc. I used a real photo of a model and tried to merge it with a picture of a 100% ai generated face, i created using Grok. I am still thinking about results. I think the sharper the reference image, more realistic and accurate is the result.
I am deliberately not mentioning, which result is from which open-source dataset. To test the waters. Pls tell me what result do you prefer. What seems more realistic ? 1, 2, or 3 ?