cjwbw/textdiffuser 🔢📝❓ → 🖼️
About
Diffusion Models as Text Painters

Example Output
Prompt:
"A sign that says 'Hello'"
Output

Performance Metrics
32.61s
Prediction Time
454.69s
Total Time
All Input Parameters
{ "prompt": "A sign that says 'Hello'", "sample_num": 1, "guidance_scale": 7.5, "num_inference_steps": 50 }
Input Parameters
- seed
- Random seed. Leave blank to randomize the seed
- prompt
- Input prompt
- sample_num
- Number of output images
- guidance_scale
- Scale for classifier-free guidance
- num_inference_steps
- Number of denoising steps
Output Schema
Output
Example Execution Logs
Using seed: 19585 encoder_hidden_states: torch.Size([1, 77, 768]). encoder_hidden_states_nocond: torch.Size([1, 77, 768]). [!] Detected keywords: ['Hello'] from prompt A sign that says 'Hello' index keyword x_min y_min x_max y_max 0 Hello 83 140 416 311 [√] Layout is successfully generated character-level segmentation_mask: torch.Size([1, 256, 256]). feature_mask: torch.Size([1, 1, 64, 64]). masked_feature: torch.Size([1, 4, 64, 64]). 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:28, 1.69it/s] 4%|▍ | 2/50 [00:01<00:27, 1.73it/s] 6%|▌ | 3/50 [00:01<00:27, 1.74it/s] 8%|▊ | 4/50 [00:02<00:26, 1.76it/s] 10%|█ | 5/50 [00:02<00:25, 1.77it/s] 12%|█▏ | 6/50 [00:03<00:24, 1.77it/s] 14%|█▍ | 7/50 [00:03<00:24, 1.77it/s] 16%|█▌ | 8/50 [00:04<00:23, 1.77it/s] 18%|█▊ | 9/50 [00:05<00:23, 1.77it/s] 20%|██ | 10/50 [00:05<00:22, 1.77it/s] 22%|██▏ | 11/50 [00:06<00:21, 1.77it/s] 24%|██▍ | 12/50 [00:06<00:21, 1.78it/s] 26%|██▌ | 13/50 [00:07<00:20, 1.78it/s] 28%|██▊ | 14/50 [00:07<00:20, 1.77it/s] 30%|███ | 15/50 [00:08<00:19, 1.77it/s] 32%|███▏ | 16/50 [00:09<00:19, 1.77it/s] 34%|███▍ | 17/50 [00:09<00:18, 1.77it/s] 36%|███▌ | 18/50 [00:10<00:18, 1.77it/s] 38%|███▊ | 19/50 [00:10<00:17, 1.77it/s] 40%|████ | 20/50 [00:11<00:17, 1.76it/s] 42%|████▏ | 21/50 [00:11<00:16, 1.76it/s] 44%|████▍ | 22/50 [00:12<00:15, 1.76it/s] 46%|████▌ | 23/50 [00:13<00:15, 1.76it/s] 48%|████▊ | 24/50 [00:13<00:14, 1.76it/s] 50%|█████ | 25/50 [00:14<00:14, 1.76it/s] 52%|█████▏ | 26/50 [00:14<00:13, 1.75it/s] 54%|█████▍ | 27/50 [00:15<00:13, 1.75it/s] 56%|█████▌ | 28/50 [00:15<00:12, 1.75it/s] 58%|█████▊ | 29/50 [00:16<00:12, 1.74it/s] 60%|██████ | 30/50 [00:17<00:11, 1.74it/s] 62%|██████▏ | 31/50 [00:17<00:10, 1.74it/s] 64%|██████▍ | 32/50 [00:18<00:10, 1.75it/s] 66%|██████▌ | 33/50 [00:18<00:09, 1.73it/s] 68%|██████▊ | 34/50 [00:19<00:09, 1.73it/s] 70%|███████ | 35/50 [00:19<00:08, 1.72it/s] 72%|███████▏ | 36/50 [00:20<00:08, 1.72it/s] 74%|███████▍ | 37/50 [00:21<00:07, 1.72it/s] 76%|███████▌ | 38/50 [00:21<00:06, 1.72it/s] 78%|███████▊ | 39/50 [00:22<00:06, 1.72it/s] 80%|████████ | 40/50 [00:22<00:05, 1.72it/s] 82%|████████▏ | 41/50 [00:23<00:05, 1.71it/s] 84%|████████▍ | 42/50 [00:24<00:04, 1.71it/s] 86%|████████▌ | 43/50 [00:24<00:04, 1.71it/s] 88%|████████▊ | 44/50 [00:25<00:03, 1.71it/s] 90%|█████████ | 45/50 [00:25<00:02, 1.70it/s] 92%|█████████▏| 46/50 [00:26<00:02, 1.70it/s] 94%|█████████▍| 47/50 [00:26<00:01, 1.70it/s] 96%|█████████▌| 48/50 [00:27<00:01, 1.70it/s] 98%|█████████▊| 49/50 [00:28<00:00, 1.69it/s] 100%|██████████| 50/50 [00:28<00:00, 1.69it/s] 100%|██████████| 50/50 [00:28<00:00, 1.74it/s]
Version Details
- Version ID
7d7fdc0954e65ee53d61dde9bc342865e0fe1e45c6f491c10e05975439c6858c
- Version Created
- June 4, 2023