biggpt1 / qwerty-logo
- Public
- 14 runs
Prediction
biggpt1/qwerty-logo:a077f67fdabbd110e6494ba48d7d4e527a8c953bb79a77a8285d22421757c862ID3mdy2zb00hrm80cmd9haz98kcrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Modern Minimalist Coffee Shop with QWRT Logo Integration “Design a sleek and modern coffee shop interior named QWERTY Coffee, featuring the unique QWRT logo as a centerpiece. The space emphasizes a minimalist aesthetic with a monochrome palette of space grey, black, and white. Key features: • Logo Integration: The QWRT logo, designed as illuminated keyboard keys, is prominently displayed behind the counter as a statement piece, with soft LED lighting adding depth. • Counter Design: A matte black counter with subtle horizontal paneling and a light glow at the base. Above, black pendant lights with frosted glass shades hang in a clean, linear arrangement. • Seating: Curved, upholstered chairs in grey and black paired with tables featuring light wood tops and sleek black bases. • Walls: Smooth concrete walls with matte black accents, including small, framed prints of abstract art and minimalist coffee-themed designs. • Lighting: Recessed ceiling lights provide ambient illumination, enhancing the sharp, clean lines of the furniture and decor. • Flooring: Polished concrete floors with a matte finish, reflecting the minimalistic design. The QWRT logo, both illuminated behind the counter and subtly placed on the menu boards, anchors the branding while blending seamlessly into the modern aesthetic
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 4
- aspect_ratio
- 16:9
- output_format
- png
- guidance_scale
- 3.28
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": " Modern Minimalist Coffee Shop with QWRT Logo Integration\n\n“Design a sleek and modern coffee shop interior named QWERTY Coffee, featuring the unique QWRT logo as a centerpiece. The space emphasizes a minimalist aesthetic with a monochrome palette of space grey, black, and white.\n\nKey features:\n\t•\tLogo Integration: The QWRT logo, designed as illuminated keyboard keys, is prominently displayed behind the counter as a statement piece, with soft LED lighting adding depth.\n\t•\tCounter Design: A matte black counter with subtle horizontal paneling and a light glow at the base. Above, black pendant lights with frosted glass shades hang in a clean, linear arrangement.\n\t•\tSeating: Curved, upholstered chairs in grey and black paired with tables featuring light wood tops and sleek black bases.\n\t•\tWalls: Smooth concrete walls with matte black accents, including small, framed prints of abstract art and minimalist coffee-themed designs.\n\t•\tLighting: Recessed ceiling lights provide ambient illumination, enhancing the sharp, clean lines of the furniture and decor.\n\t•\tFlooring: Polished concrete floors with a matte finish, reflecting the minimalistic design.\n\nThe QWRT logo, both illuminated behind the counter and subtly placed on the menu boards, anchors the branding while blending seamlessly into the modern aesthetic", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.28, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run biggpt1/qwerty-logo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "biggpt1/qwerty-logo:a077f67fdabbd110e6494ba48d7d4e527a8c953bb79a77a8285d22421757c862", { input: { model: "dev", prompt: " Modern Minimalist Coffee Shop with QWRT Logo Integration\n\n“Design a sleek and modern coffee shop interior named QWERTY Coffee, featuring the unique QWRT logo as a centerpiece. The space emphasizes a minimalist aesthetic with a monochrome palette of space grey, black, and white.\n\nKey features:\n\t•\tLogo Integration: The QWRT logo, designed as illuminated keyboard keys, is prominently displayed behind the counter as a statement piece, with soft LED lighting adding depth.\n\t•\tCounter Design: A matte black counter with subtle horizontal paneling and a light glow at the base. Above, black pendant lights with frosted glass shades hang in a clean, linear arrangement.\n\t•\tSeating: Curved, upholstered chairs in grey and black paired with tables featuring light wood tops and sleek black bases.\n\t•\tWalls: Smooth concrete walls with matte black accents, including small, framed prints of abstract art and minimalist coffee-themed designs.\n\t•\tLighting: Recessed ceiling lights provide ambient illumination, enhancing the sharp, clean lines of the furniture and decor.\n\t•\tFlooring: Polished concrete floors with a matte finish, reflecting the minimalistic design.\n\nThe QWRT logo, both illuminated behind the counter and subtly placed on the menu boards, anchors the branding while blending seamlessly into the modern aesthetic", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 4, aspect_ratio: "16:9", output_format: "png", guidance_scale: 3.28, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run biggpt1/qwerty-logo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "biggpt1/qwerty-logo:a077f67fdabbd110e6494ba48d7d4e527a8c953bb79a77a8285d22421757c862", input={ "model": "dev", "prompt": " Modern Minimalist Coffee Shop with QWRT Logo Integration\n\n“Design a sleek and modern coffee shop interior named QWERTY Coffee, featuring the unique QWRT logo as a centerpiece. The space emphasizes a minimalist aesthetic with a monochrome palette of space grey, black, and white.\n\nKey features:\n\t•\tLogo Integration: The QWRT logo, designed as illuminated keyboard keys, is prominently displayed behind the counter as a statement piece, with soft LED lighting adding depth.\n\t•\tCounter Design: A matte black counter with subtle horizontal paneling and a light glow at the base. Above, black pendant lights with frosted glass shades hang in a clean, linear arrangement.\n\t•\tSeating: Curved, upholstered chairs in grey and black paired with tables featuring light wood tops and sleek black bases.\n\t•\tWalls: Smooth concrete walls with matte black accents, including small, framed prints of abstract art and minimalist coffee-themed designs.\n\t•\tLighting: Recessed ceiling lights provide ambient illumination, enhancing the sharp, clean lines of the furniture and decor.\n\t•\tFlooring: Polished concrete floors with a matte finish, reflecting the minimalistic design.\n\nThe QWRT logo, both illuminated behind the counter and subtly placed on the menu boards, anchors the branding while blending seamlessly into the modern aesthetic", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.28, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run biggpt1/qwerty-logo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "biggpt1/qwerty-logo:a077f67fdabbd110e6494ba48d7d4e527a8c953bb79a77a8285d22421757c862", "input": { "model": "dev", "prompt": " Modern Minimalist Coffee Shop with QWRT Logo Integration\\n\\n“Design a sleek and modern coffee shop interior named QWERTY Coffee, featuring the unique QWRT logo as a centerpiece. The space emphasizes a minimalist aesthetic with a monochrome palette of space grey, black, and white.\\n\\nKey features:\\n\\t•\\tLogo Integration: The QWRT logo, designed as illuminated keyboard keys, is prominently displayed behind the counter as a statement piece, with soft LED lighting adding depth.\\n\\t•\\tCounter Design: A matte black counter with subtle horizontal paneling and a light glow at the base. Above, black pendant lights with frosted glass shades hang in a clean, linear arrangement.\\n\\t•\\tSeating: Curved, upholstered chairs in grey and black paired with tables featuring light wood tops and sleek black bases.\\n\\t•\\tWalls: Smooth concrete walls with matte black accents, including small, framed prints of abstract art and minimalist coffee-themed designs.\\n\\t•\\tLighting: Recessed ceiling lights provide ambient illumination, enhancing the sharp, clean lines of the furniture and decor.\\n\\t•\\tFlooring: Polished concrete floors with a matte finish, reflecting the minimalistic design.\\n\\nThe QWRT logo, both illuminated behind the counter and subtly placed on the menu boards, anchors the branding while blending seamlessly into the modern aesthetic", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.28, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-01-15T14:34:12.319600Z", "created_at": "2025-01-15T14:33:39.588000Z", "data_removed": false, "error": null, "id": "3mdy2zb00hrm80cmd9haz98kcr", "input": { "model": "dev", "prompt": " Modern Minimalist Coffee Shop with QWRT Logo Integration\n\n“Design a sleek and modern coffee shop interior named QWERTY Coffee, featuring the unique QWRT logo as a centerpiece. The space emphasizes a minimalist aesthetic with a monochrome palette of space grey, black, and white.\n\nKey features:\n\t•\tLogo Integration: The QWRT logo, designed as illuminated keyboard keys, is prominently displayed behind the counter as a statement piece, with soft LED lighting adding depth.\n\t•\tCounter Design: A matte black counter with subtle horizontal paneling and a light glow at the base. Above, black pendant lights with frosted glass shades hang in a clean, linear arrangement.\n\t•\tSeating: Curved, upholstered chairs in grey and black paired with tables featuring light wood tops and sleek black bases.\n\t•\tWalls: Smooth concrete walls with matte black accents, including small, framed prints of abstract art and minimalist coffee-themed designs.\n\t•\tLighting: Recessed ceiling lights provide ambient illumination, enhancing the sharp, clean lines of the furniture and decor.\n\t•\tFlooring: Polished concrete floors with a matte finish, reflecting the minimalistic design.\n\nThe QWRT logo, both illuminated behind the counter and subtly placed on the menu boards, anchors the branding while blending seamlessly into the modern aesthetic", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "16:9", "output_format": "png", "guidance_scale": 3.28, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-15 14:33:45.889 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-15 14:33:45.890 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2770.29it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2693.32it/s]\n2025-01-15 14:33:46.003 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=28379331031040\nDownloading weights\n2025-01-15T14:33:46Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv0il1ekh/weights url=https://replicate.delivery/xezq/1eNzmGanfVkMTUTWdS8m8plk5lDNlV48hSH8h2EOEJNbiXFUA/trained_model.tar\n2025-01-15T14:33:47Z | INFO | [ Complete ] dest=/tmp/tmpv0il1ekh/weights size=\"215 MB\" total_elapsed=1.399s url=https://replicate.delivery/xezq/1eNzmGanfVkMTUTWdS8m8plk5lDNlV48hSH8h2EOEJNbiXFUA/trained_model.tar\nDownloaded weights in 1.42s\n2025-01-15 14:33:47.430 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/0b05f0078626c941\n2025-01-15 14:33:47.514 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-15 14:33:47.514 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-15 14:33:47.515 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 96%|█████████▋| 293/304 [00:00<00:00, 2927.04it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2884.42it/s]\n2025-01-15 14:33:47.620 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 34509\n0it [00:00, ?it/s]\n1it [00:00, 8.48it/s]\n2it [00:00, 5.94it/s]\n3it [00:00, 5.41it/s]\n4it [00:00, 5.19it/s]\n5it [00:00, 5.07it/s]\n6it [00:01, 4.97it/s]\n7it [00:01, 4.93it/s]\n8it [00:01, 4.92it/s]\n9it [00:01, 4.91it/s]\n10it [00:01, 4.89it/s]\n11it [00:02, 4.86it/s]\n12it [00:02, 4.85it/s]\n13it [00:02, 4.84it/s]\n14it [00:02, 4.84it/s]\n15it [00:03, 4.83it/s]\n16it [00:03, 4.83it/s]\n17it [00:03, 4.83it/s]\n18it [00:03, 4.84it/s]\n19it [00:03, 4.83it/s]\n20it [00:04, 4.83it/s]\n21it [00:04, 4.82it/s]\n22it [00:04, 4.83it/s]\n23it [00:04, 4.83it/s]\n24it [00:04, 4.83it/s]\n25it [00:05, 4.83it/s]\n26it [00:05, 4.82it/s]\n27it [00:05, 4.83it/s]\n28it [00:05, 4.82it/s]\n28it [00:05, 4.91it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.87it/s]\n2it [00:00, 4.86it/s]\n3it [00:00, 4.85it/s]\n4it [00:00, 4.84it/s]\n5it [00:01, 4.84it/s]\n6it [00:01, 4.85it/s]\n7it [00:01, 4.85it/s]\n8it [00:01, 4.85it/s]\n9it [00:01, 4.84it/s]\n10it [00:02, 4.85it/s]\n11it [00:02, 4.84it/s]\n12it [00:02, 4.84it/s]\n13it [00:02, 4.85it/s]\n14it [00:02, 4.85it/s]\n15it [00:03, 4.85it/s]\n16it [00:03, 4.85it/s]\n17it [00:03, 4.85it/s]\n18it [00:03, 4.85it/s]\n19it [00:03, 4.85it/s]\n20it [00:04, 4.84it/s]\n21it [00:04, 4.84it/s]\n22it [00:04, 4.85it/s]\n23it [00:04, 4.85it/s]\n24it [00:04, 4.86it/s]\n25it [00:05, 4.86it/s]\n26it [00:05, 4.86it/s]\n27it [00:05, 4.85it/s]\n28it [00:05, 4.84it/s]\n28it [00:05, 4.85it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.87it/s]\n2it [00:00, 4.82it/s]\n3it [00:00, 4.82it/s]\n4it [00:00, 4.80it/s]\n5it [00:01, 4.82it/s]\n6it [00:01, 4.84it/s]\n7it [00:01, 4.84it/s]\n8it [00:01, 4.85it/s]\n9it [00:01, 4.85it/s]\n10it [00:02, 4.85it/s]\n11it [00:02, 4.85it/s]\n12it [00:02, 4.85it/s]\n13it [00:02, 4.85it/s]\n14it [00:02, 4.85it/s]\n15it [00:03, 4.86it/s]\n16it [00:03, 4.86it/s]\n17it [00:03, 4.85it/s]\n18it [00:03, 4.84it/s]\n19it [00:03, 4.85it/s]\n20it [00:04, 4.85it/s]\n21it [00:04, 4.85it/s]\n22it [00:04, 4.85it/s]\n23it [00:04, 4.84it/s]\n24it [00:04, 4.84it/s]\n25it [00:05, 4.85it/s]\n26it [00:05, 4.85it/s]\n27it [00:05, 4.84it/s]\n28it [00:05, 4.85it/s]\n28it [00:05, 4.84it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.87it/s]\n2it [00:00, 4.87it/s]\n3it [00:00, 4.83it/s]\n4it [00:00, 4.82it/s]\n5it [00:01, 4.79it/s]\n6it [00:01, 4.78it/s]\n7it [00:01, 4.79it/s]\n8it [00:01, 4.81it/s]\n9it [00:01, 4.82it/s]\n10it [00:02, 4.82it/s]\n11it [00:02, 4.81it/s]\n12it [00:02, 4.81it/s]\n13it [00:02, 4.81it/s]\n14it [00:02, 4.80it/s]\n15it [00:03, 4.81it/s]\n16it [00:03, 4.81it/s]\n17it [00:03, 4.81it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.82it/s]\n20it [00:04, 4.83it/s]\n21it [00:04, 4.84it/s]\n22it [00:04, 4.83it/s]\n23it [00:04, 4.84it/s]\n24it [00:04, 4.84it/s]\n25it [00:05, 4.84it/s]\n26it [00:05, 4.84it/s]\n27it [00:05, 4.84it/s]\n28it [00:05, 4.84it/s]\n28it [00:05, 4.82it/s]\nTotal safe images: 4 out of 4", "metrics": { "predict_time": 26.428874511, "total_time": 32.7316 }, "output": [ "https://replicate.delivery/xezq/lDDwRHexJnWcFSoV3dn59bdvNZNYcZlq5ht4OJLtQ2SyyrCKA/out-0.png", "https://replicate.delivery/xezq/xAd02FRdD2LsItN8zfUP51vXZdXTkOpT92WKlZPykrYyyrCKA/out-1.png", "https://replicate.delivery/xezq/lfed4ibzwilhi0IlEWfuOlqDRfLhYIKQh4Pueoen9mGHZ5VBF/out-2.png", "https://replicate.delivery/xezq/9HBIQjo6xq4OH9E5Dr3yZhBeiyMv9DFKRuvhRuTNPzUyyrCKA/out-3.png" ], "started_at": "2025-01-15T14:33:45.890725Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-yjqgnttg55gkrrzxbmr7e7eroayl4cwgljlsoa7a2evvhky5ajha", "get": "https://api.replicate.com/v1/predictions/3mdy2zb00hrm80cmd9haz98kcr", "cancel": "https://api.replicate.com/v1/predictions/3mdy2zb00hrm80cmd9haz98kcr/cancel" }, "version": "a077f67fdabbd110e6494ba48d7d4e527a8c953bb79a77a8285d22421757c862" }
Generated in2025-01-15 14:33:45.889 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-15 14:33:45.890 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2770.29it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2693.32it/s] 2025-01-15 14:33:46.003 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=28379331031040 Downloading weights 2025-01-15T14:33:46Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv0il1ekh/weights url=https://replicate.delivery/xezq/1eNzmGanfVkMTUTWdS8m8plk5lDNlV48hSH8h2EOEJNbiXFUA/trained_model.tar 2025-01-15T14:33:47Z | INFO | [ Complete ] dest=/tmp/tmpv0il1ekh/weights size="215 MB" total_elapsed=1.399s url=https://replicate.delivery/xezq/1eNzmGanfVkMTUTWdS8m8plk5lDNlV48hSH8h2EOEJNbiXFUA/trained_model.tar Downloaded weights in 1.42s 2025-01-15 14:33:47.430 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/0b05f0078626c941 2025-01-15 14:33:47.514 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-15 14:33:47.514 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-15 14:33:47.515 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 96%|█████████▋| 293/304 [00:00<00:00, 2927.04it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2884.42it/s] 2025-01-15 14:33:47.620 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 34509 0it [00:00, ?it/s] 1it [00:00, 8.48it/s] 2it [00:00, 5.94it/s] 3it [00:00, 5.41it/s] 4it [00:00, 5.19it/s] 5it [00:00, 5.07it/s] 6it [00:01, 4.97it/s] 7it [00:01, 4.93it/s] 8it [00:01, 4.92it/s] 9it [00:01, 4.91it/s] 10it [00:01, 4.89it/s] 11it [00:02, 4.86it/s] 12it [00:02, 4.85it/s] 13it [00:02, 4.84it/s] 14it [00:02, 4.84it/s] 15it [00:03, 4.83it/s] 16it [00:03, 4.83it/s] 17it [00:03, 4.83it/s] 18it [00:03, 4.84it/s] 19it [00:03, 4.83it/s] 20it [00:04, 4.83it/s] 21it [00:04, 4.82it/s] 22it [00:04, 4.83it/s] 23it [00:04, 4.83it/s] 24it [00:04, 4.83it/s] 25it [00:05, 4.83it/s] 26it [00:05, 4.82it/s] 27it [00:05, 4.83it/s] 28it [00:05, 4.82it/s] 28it [00:05, 4.91it/s] 0it [00:00, ?it/s] 1it [00:00, 4.87it/s] 2it [00:00, 4.86it/s] 3it [00:00, 4.85it/s] 4it [00:00, 4.84it/s] 5it [00:01, 4.84it/s] 6it [00:01, 4.85it/s] 7it [00:01, 4.85it/s] 8it [00:01, 4.85it/s] 9it [00:01, 4.84it/s] 10it [00:02, 4.85it/s] 11it [00:02, 4.84it/s] 12it [00:02, 4.84it/s] 13it [00:02, 4.85it/s] 14it [00:02, 4.85it/s] 15it [00:03, 4.85it/s] 16it [00:03, 4.85it/s] 17it [00:03, 4.85it/s] 18it [00:03, 4.85it/s] 19it [00:03, 4.85it/s] 20it [00:04, 4.84it/s] 21it [00:04, 4.84it/s] 22it [00:04, 4.85it/s] 23it [00:04, 4.85it/s] 24it [00:04, 4.86it/s] 25it [00:05, 4.86it/s] 26it [00:05, 4.86it/s] 27it [00:05, 4.85it/s] 28it [00:05, 4.84it/s] 28it [00:05, 4.85it/s] 0it [00:00, ?it/s] 1it [00:00, 4.87it/s] 2it [00:00, 4.82it/s] 3it [00:00, 4.82it/s] 4it [00:00, 4.80it/s] 5it [00:01, 4.82it/s] 6it [00:01, 4.84it/s] 7it [00:01, 4.84it/s] 8it [00:01, 4.85it/s] 9it [00:01, 4.85it/s] 10it [00:02, 4.85it/s] 11it [00:02, 4.85it/s] 12it [00:02, 4.85it/s] 13it [00:02, 4.85it/s] 14it [00:02, 4.85it/s] 15it [00:03, 4.86it/s] 16it [00:03, 4.86it/s] 17it [00:03, 4.85it/s] 18it [00:03, 4.84it/s] 19it [00:03, 4.85it/s] 20it [00:04, 4.85it/s] 21it [00:04, 4.85it/s] 22it [00:04, 4.85it/s] 23it [00:04, 4.84it/s] 24it [00:04, 4.84it/s] 25it [00:05, 4.85it/s] 26it [00:05, 4.85it/s] 27it [00:05, 4.84it/s] 28it [00:05, 4.85it/s] 28it [00:05, 4.84it/s] 0it [00:00, ?it/s] 1it [00:00, 4.87it/s] 2it [00:00, 4.87it/s] 3it [00:00, 4.83it/s] 4it [00:00, 4.82it/s] 5it [00:01, 4.79it/s] 6it [00:01, 4.78it/s] 7it [00:01, 4.79it/s] 8it [00:01, 4.81it/s] 9it [00:01, 4.82it/s] 10it [00:02, 4.82it/s] 11it [00:02, 4.81it/s] 12it [00:02, 4.81it/s] 13it [00:02, 4.81it/s] 14it [00:02, 4.80it/s] 15it [00:03, 4.81it/s] 16it [00:03, 4.81it/s] 17it [00:03, 4.81it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.82it/s] 20it [00:04, 4.83it/s] 21it [00:04, 4.84it/s] 22it [00:04, 4.83it/s] 23it [00:04, 4.84it/s] 24it [00:04, 4.84it/s] 25it [00:05, 4.84it/s] 26it [00:05, 4.84it/s] 27it [00:05, 4.84it/s] 28it [00:05, 4.84it/s] 28it [00:05, 4.82it/s] Total safe images: 4 out of 4
Want to make some of these yourself?
Run this model