dekaselinos/cartoon_90s_style 🖼️🔢❓📝✓ → 🖼️
About
Transforms pet photos into high-quality 90s Disney-style cartoon illustrations with accurate fur details and charming expressions.

Example Output
Prompt:
"disneycartoon style, full-body portrait of an adorable Golden Retriever dog, clearly recognizable as a Golden Retriever, with accurate fur color and texture based on the uploaded image, joyful and expressive facial expression, smooth line art, soft shading, fluffy coat, big round eyes, Pixar-quality character design, clean vibrant background, classic hand-drawn Disney animation style, detailed 2D cartoon illustration"
Output

Performance Metrics
13.02s
Prediction Time
13.10s
Total Time
All Input Parameters
{ "image": "https://replicate.delivery/pbxt/NIwqRHOKgK1MZsKpxGXFODhThaFrUbTV6zVv1k0uVdr3kNkD/pexels-svetozar-milashevich-99573-1490908.jpg", "model": "dev", "prompt": "disneycartoon style, full-body portrait of an adorable Golden Retriever dog, clearly recognizable as a Golden Retriever, with accurate fur color and texture based on the uploaded image, joyful and expressive facial expression, smooth line art, soft shading, fluffy coat, big round eyes, Pixar-quality character design, clean vibrant background, classic hand-drawn Disney animation style, detailed 2D cartoon illustration", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Input Parameters
- mask
- Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- seed
- Random seed. Set for reproducible generation
- image
- Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- model
- Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.
- width
- Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- height
- Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- prompt (required)
- Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.
- go_fast
- Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
- extra_lora
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- lora_scale
- Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- megapixels
- Approximate number of megapixels for generated image
- num_outputs
- Number of outputs to generate
- aspect_ratio
- Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
- output_format
- Format of the output images
- guidance_scale
- Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5
- output_quality
- Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
- prompt_strength
- Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
- extra_lora_scale
- Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- replicate_weights
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- num_inference_steps
- Number of denoising steps. More steps can give more detailed images, but take longer.
- disable_safety_checker
- Disable safety checker for generated images.
Output Schema
Output
Example Execution Logs
free=24500740259840 Downloading weights 2025-07-05T11:36:41Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpnqe8atdw/weights url=https://replicate.delivery/xezq/zGPlv5AAFzqhIdeA3JUqOTvH1YzXEcaHUlW8oCQMmt2KfI9UA/flux-lora.tar 2025-07-05T11:36:41Z | INFO | [ Cache Service ] enabled=true scheme=http target=hermes.services.svc.cluster.local 2025-07-05T11:36:41Z | INFO | [ Cache URL Rewrite ] enabled=true target_url=http://hermes.services.svc.cluster.local/replicate.delivery/xezq/zGPlv5AAFzqhIdeA3JUqOTvH1YzXEcaHUlW8oCQMmt2KfI9UA/flux-lora.tar url=https://replicate.delivery/xezq/zGPlv5AAFzqhIdeA3JUqOTvH1YzXEcaHUlW8oCQMmt2KfI9UA/flux-lora.tar 2025-07-05T11:36:41Z | INFO | [ Redirect ] redirect_url=http://r8-east4-loras-ric1.cwlota.com/e94f4f8e0494936aa332cb115bde44c25af4bc47092efdb318b957aa03087050?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Checksum-Mode=ENABLED&X-Amz-Credential=CWNZUVKLDHXVHEZN%2F20250705%2FUS-EAST-04A%2Fs3%2Faws4_request&X-Amz-Date=20250705T113641Z&X-Amz-Expires=600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=f7586a20e93ba4322f0d0dba192d8dc2f23892a1a22f6c52580a31c307479a2f url=http://hermes.services.svc.cluster.local/replicate.delivery/xezq/zGPlv5AAFzqhIdeA3JUqOTvH1YzXEcaHUlW8oCQMmt2KfI9UA/flux-lora.tar 2025-07-05T11:36:41Z | INFO | [ Complete ] dest=/tmp/tmpnqe8atdw/weights size="172 MB" total_elapsed=0.244s url=https://replicate.delivery/xezq/zGPlv5AAFzqhIdeA3JUqOTvH1YzXEcaHUlW8oCQMmt2KfI9UA/flux-lora.tar Downloaded weights in 0.30s Loaded LoRAs in 2.74s Using seed: 20747 Prompt: disneycartoon style, full-body portrait of an adorable Golden Retriever dog, clearly recognizable as a Golden Retriever, with accurate fur color and texture based on the uploaded image, joyful and expressive facial expression, smooth line art, soft shading, fluffy coat, big round eyes, Pixar-quality character design, clean vibrant background, classic hand-drawn Disney animation style, detailed 2D cartoon illustration Input image size: 6000x4000 [!] Resizing input image from 6000x4000 to 1440x960 [!] img2img mode 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:06, 3.61it/s] 9%|▊ | 2/23 [00:00<00:06, 3.14it/s] 13%|█▎ | 3/23 [00:00<00:06, 3.01it/s] 17%|█▋ | 4/23 [00:01<00:06, 2.95it/s] 22%|██▏ | 5/23 [00:01<00:06, 2.92it/s] 26%|██▌ | 6/23 [00:02<00:05, 2.90it/s] 30%|███ | 7/23 [00:02<00:05, 2.89it/s] 35%|███▍ | 8/23 [00:02<00:05, 2.88it/s] 39%|███▉ | 9/23 [00:03<00:04, 2.88it/s] 43%|████▎ | 10/23 [00:03<00:04, 2.88it/s] 48%|████▊ | 11/23 [00:03<00:04, 2.88it/s] 52%|█████▏ | 12/23 [00:04<00:03, 2.87it/s] 57%|█████▋ | 13/23 [00:04<00:03, 2.87it/s] 61%|██████ | 14/23 [00:04<00:03, 2.87it/s] 65%|██████▌ | 15/23 [00:05<00:02, 2.87it/s] 70%|██████▉ | 16/23 [00:05<00:02, 2.87it/s] 74%|███████▍ | 17/23 [00:05<00:02, 2.86it/s] 78%|███████▊ | 18/23 [00:06<00:01, 2.87it/s] 83%|████████▎ | 19/23 [00:06<00:01, 2.87it/s] 87%|████████▋ | 20/23 [00:06<00:01, 2.86it/s] 91%|█████████▏| 21/23 [00:07<00:00, 2.86it/s] 96%|█████████▌| 22/23 [00:07<00:00, 2.87it/s] 100%|██████████| 23/23 [00:07<00:00, 2.87it/s] 100%|██████████| 23/23 [00:07<00:00, 2.89it/s] Total safe images: 1 out of 1
Version Details
- Version ID
0fa908602ef6c6259b41f5b8d8c14956252cbf197897cce9adb21e8d16478ed0
- Version Created
- July 3, 2025