subhash25rawat/custom-hair 🖼️ → 🖼️
About
Customise your hair with AI. Swap hair with anyone, copy anyone's hair color.
Example Output
Output
Performance Metrics
45.17s
Prediction Time
335.56s
Total Time
All Input Parameters
{
"face_image": "https://replicate.delivery/pbxt/MPV6rRRX2WVexpahBMcYL9qRnFQg8XsISFV1CUgwvcrUQ4WJ/29995.png",
"hair_image": "https://replicate.delivery/pbxt/MPV6s0mFWBBE6SjmhRADZSv02YWpKF4KYk5KisZDutqTILI3/06041.png",
"color_image": "https://replicate.delivery/pbxt/MPV6rd7oS2paLzlwjtFJ1tK8ArjLUK6RCu7QVUO3hLkR6AOH/29995.png"
}
Input Parameters
- face_image (required)
- Image of the person whose hair style is to be changed
- hair_image (required)
- Image of the person whose hair style is to be copied
- color_image
- Image of the person whose hair color is to be copied
Output Schema
Output
Example Execution Logs
Original image size: 1024x1024 Resized image size: 720x720 Image pasted at: 0, 0 Original image size: 1024x1024 Resized image size: 720x720 Image pasted at: 0, 0 Original image size: 1024x1024 Resized image size: 720x720 Image pasted at: 0, 0 Number of faces detected: 1 Number of faces detected: 1 Loading StyleGAN2 from checkpoint: pretrained_models/StyleGAN/ffhq.pt Downloading: "https://download.pytorch.org/models/resnet18-5c106cde.pth" to /root/.cache/torch/hub/checkpoints/resnet18-5c106cde.pth 0%| | 0.00/44.7M [00:00<?, ?B/s] 21%|██ | 9.45M/44.7M [00:00<00:00, 99.1MB/s] 78%|███████▊ | 34.7M/44.7M [00:00<00:00, 196MB/s] 100%|██████████| 44.7M/44.7M [00:00<00:00, 195MB/s] Loading e4e over the pSp framework from checkpoint: pretrained_models/encoder4editing/e4e_ffhq_encode.pt Network [SPADEGenerator] was created. Total number of parameters: 266.9 million. To see the architecture, do print(network). 0%| | 0.00/335M [00:00<?, ?iB/s] 2%|▉ | 8.03M/335M [00:00<00:04, 83.5MiB/s] 5%|█▉ | 17.4M/335M [00:00<00:03, 91.8MiB/s] 9%|███▍ | 29.3M/335M [00:00<00:02, 107MiB/s] 13%|█████▏ | 44.4M/335M [00:00<00:02, 127MiB/s] 17%|██████▌ | 56.5M/335M [00:00<00:02, 105MiB/s] 20%|███████▌ | 67.0M/335M [00:00<00:03, 85.9MiB/s] 24%|████████▉ | 79.0M/335M [00:00<00:02, 96.2MiB/s] 28%|███████████ | 94.4M/335M [00:00<00:02, 114MiB/s] 32%|████████████▋ | 106M/335M [00:01<00:02, 110MiB/s] 35%|██████████████ | 117M/335M [00:01<00:02, 105MiB/s] 38%|███████████████▏ | 128M/335M [00:01<00:02, 105MiB/s] 43%|█████████████████ | 143M/335M [00:01<00:01, 121MiB/s] 46%|██████████████████▌ | 155M/335M [00:01<00:01, 121MiB/s] 50%|███████████████████▉ | 167M/335M [00:01<00:01, 115MiB/s] 53%|█████████████████████▎ | 178M/335M [00:01<00:01, 101MiB/s] 56%|█████████████████████▉ | 188M/335M [00:01<00:01, 96.5MiB/s] 59%|███████████████████████ | 198M/335M [00:01<00:01, 96.4MiB/s] 62%|████████████████████████▏ | 207M/335M [00:02<00:01, 94.3MiB/s] 65%|█████████████████████████▏ | 217M/335M [00:02<00:01, 95.3MiB/s] 68%|███████████████████████████▏ | 227M/335M [00:02<00:01, 101MiB/s] 71%|███████████████████████████▋ | 237M/335M [00:02<00:01, 97.8MiB/s] 74%|█████████████████████████████▌ | 247M/335M [00:02<00:00, 101MiB/s] 77%|██████████████████████████████▊ | 258M/335M [00:02<00:00, 104MiB/s] 80%|███████████████████████████████▏ | 268M/335M [00:02<00:00, 89.6MiB/s] 83%|████████████████████████████████▎ | 277M/335M [00:02<00:00, 72.5MiB/s] 86%|█████████████████████████████████▍ | 287M/335M [00:03<00:00, 80.4MiB/s] 89%|██████████████████████████████████▉ | 299M/335M [00:03<00:00, 92.7MiB/s] 93%|████████████████████████████████████▏ | 310M/335M [00:03<00:00, 98.3MiB/s] 96%|██████████████████████████████████████▌ | 322M/335M [00:03<00:00, 106MiB/s] 100%|████████████████████████████████████████| 335M/335M [00:03<00:00, 102MiB/s] 0%| | 0/1 [00:00<?, ?it/s] 0%| | 0/1 [00:04<?, ?it/s]
Version Details
- Version ID
79fcdf78d664c6f7bfd2468fdd3db2ba514bf5d777300f951f5e4b19cdbdbb5f- Version Created
- January 29, 2025