![\"0fb4fb07j00tjl1s600owd000p200e4p\"](\"https:\/\/www.1ai.net\/wp-content\/uploads\/2026\/08\/0fb4fb07j00tjl1s600owd000p200e4p.jpg\" "\\"0fb4fb07j00tjl1s600owd000p200e4p\\"")
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In the first seven, you've been able to report mistakes from zero, graphics, quality, self-help. But there's a problem: every time you get a hard \"squeeze\" from a text phrase, you want a picture, you want a position, you can't describe it simply by words\u3002<\/p>\n
This is the timefigure (img2img)<\/strong>OKAY. I DISCOVERED THAT THIS FUNCTION OPENED UP A NEW WORLD -- TO TAKE AN OFF-THE-SHELF PICTURE AS THE BOTTOM, TO MAKE AI CHANGE IT, 10 TIMES MORE EFFICIENT THAN A HINT FROM ZERO. THIS HAND-AND-HAND PIECE TEACHES YOU: WHAT'S GOING ON WITH THE DRAWINGS, HOW TO ADJUST THE NOISE INTENSITY, AND HOW TO COPY THREE REAL-WORLD SCENES\u3002<\/p>\n I. HOW THE THOSE graphS ARE<\/strong><\/p>\n One sentence:Fig = Vincent + a reference graph<\/strong>I don't know. The Vensheng map is \"Playing from noise\" and the drawing is \"Encoded into subspace and recreated on this basis\". Key node chain:<\/p>\n Load Image Most critical pits:<\/strong>KSampler's last_image\u00a0VAE Encode output<\/strong>It's not that part of Vincent's. I've seen the new guy connect the original to KSampler, and the result is noise -- the pixels are not coded by VAE, AI when the pure noise is processed. The original map must pass VAE Encode to feed KSampler\u3002<\/p>\n ii. Noise intensity reduction<\/strong><\/p>\n denoise decided \u201cto retain the original figure\u201d\u30020 = the original image remains intact, 1 = the total noise replacement (equivalent to the texture)<\/strong>.<\/p>\n think of \"same style\" and \"denoise\"\u00a00.4<\/strong>\u00a0The most comfy -- the image is still there, the style is changing. First-time starter with 0.5, with 0.1 for each turn. There is a difference between SDXL and Flux: Flux submersible space is more compressed than it is available at 0.8 to 0.95; SDXL is more appropriate at 0.2 to 0.4\u3002<\/p>\n Trail experience:<\/strong>For the first time, I made a map of denoise = 0.1, which is almost exactly the same as the original one, and thought the work flow was broken. Later on -- the lower the denoise, the lower the AI changes, the lower the 0.1 is basically the same\u3002<\/p>\n iii. Put your hand on a map<\/strong><\/p>\n And the 05 base graphics, only two more points\u3002 10 minutes, change your picture to Sabpunk<\/strong><\/p>\n That's the truth. After you've got one more picture of your photo turned into Saberpunk, you'll be able to confirm that Tusheng is real\u3002<\/p>\n Preconditions<\/strong>: You've got the 05th Basic Chart Workstream. Lose it again\u3002 Step (sight, don't jump): Checkpoint<\/strong><\/p>\n One is also the position of the \"you\" and the position of the face, but the colored background is full of Sabpunk<\/p>\n 2 acoustic noise, 80% KSampler still picks up Emtty Latet, not VAE Encode output (back to pit III)<\/p>\n 3 same as original figure 80% denoise too low (<0.2), pull back 0.6\u3002<\/p>\n job (chosen): the same photo, denoise sets a comparison of 0.3 and 0.8, respectively. it's \"little change\" and it's \"most retrospects with only a contours\" -- it's a denoise spin\u3002<\/p>\n Four, three real battlefield scenarios<\/strong><\/p>\n The principle and the tie-up, the three most common scenes below, the hints and parameters are written, and you change your own picture\u3002<\/p>\n scene one: Photo to art<\/strong><\/p>\n positive: cyberpunk style, new lights, light, city stage, masterpece, best quality scene two: line colour<\/strong><\/p>\n positive: colored, vibrant colors, anime style+ specific colours\u3002 Scenario III: Old Photo Restoration \/ Clear<\/strong><\/p>\n right in the middle of the day Can play:Plot<\/strong>(the sketch is the bottom, denoise 0.5 ~ 0.7)Variable<\/strong>(Same hint: 0.35 to 0.7 for the best)Partial repaint<\/strong>(Mask white = change of area, next section)\u3002<\/p>\n V. QUIREMENTS OF PARLIAMENTS (Scene by scene)<\/strong><\/p>\n VI. 4060 \/ 8G TECHNIQUE & PIT I STEPPED ON<\/strong><\/p>\n Skills: Visible storage resolution 28G BASE MAP FROM 512X512<\/strong>, with a small hyphenation and magnification; donoise not too much time; and a sampler with Euler \/ LCM is lighter\u3002<\/p>\n Pit 1:\u00a0denoise = 1 free<\/strong>, equals the Ventura map\u00a0The size doesn't match the model<\/strong>, pre-scaling originals; 3\u00a0Confusion between denoise and CFG<\/strong>The former retains the original figure and the latter hears the hint\u3002<\/p>\n Tusk will, you can take any chart as a springboard. NextTitle 09<\/strong>SpeakRORA USE ACTUALLY<\/strong>\u2013 How to select, lower, lower, and string weights so that the \"Build-the-Build-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Class-Cass-Cass-Cas-Cas-Cas-Cass-Cor-Cas-Cas-Cas-Cas-Cas-Ced-Cas-Cs-Cas-C\u3002<\/p>","protected":false},"excerpt":{"rendered":" In the first seven, you've been able to report mistakes from zero, graphics, quality, self-help. But there's a problem: every time you get a hard \"squeeze\" from a text phrase, you want a picture, you want a position, you can't describe it simply by words. It's time for meg2img. I discovered that this function opened up a new world -- to take an off-the-shelf picture as the bottom, to make AI change it, 10 times more efficient than a hint from zero. This hand-and-hand piece teaches you: what's going on with the drawings, how to adjust the noise intensity, and how to copy three real-world scenes. I. What the hell is this? Vincent's drawings are \"a blank drawing from the noise.\"<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[149,144],"tags":[1989,6276,4749],"collection":[],"class_list":["post-55760","post","type-post","status-publish","format-standard","hentry","category-jiaocheng","category-baike","tag-comfyui"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/55760","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=55760"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/55760\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=55760"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=55760"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=55760"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=55760"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nVAE Encode (encoded subspace)
\nKSampler
\nVAE Decode
\nSave Image<\/p>\n\n\n
\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\n1.\u00a0Add Road Image<\/strong>: Bottomchart (or drag to nodes)\u3002
\n2.\u00a0Add VAE Encode<\/strong>: Load Image IMAGE company pixels, Checkpoint VAE company vae\u3002
\n3.\u00a0Add KSampler<\/strong>: VAE Encode's LATENT Company League_image Not Emtty Latet\u3002
\n4.\u00a0Add VAE Decode + Save Image<\/strong>An identical map\u3002
\n5.\u00a0Run<\/strong>Queue Prompt\u3002<\/p>\n
\nTarget<\/strong>Take a photo of yourself and change it to Cyberpunk and keep the original image\u3002<\/p>\n
\n1.\u00a0Chart<\/strong>: Find a picture of yourself (the best man) and put it on the table\u3002
\n2.\u00a0Add Road Image<\/strong>: Double-click blanks in the canvas search Load Image return car node \"choose file\" select photos (or drag a map into the node)\u3002
\n3.\u00a0Add VAE Encode<\/strong>: Load Image IMAGE company pixels, Checkpoint VAE company vae\u3002
\n4.\u00a0Reconnection (most critical)<\/strong>: unplugged the original KSampler Emtty Latent and reconnected to the VAE Encode's Latent_image; set for denoise 0.6\u3002
\n5.\u00a0Write hints<\/strong>: negative emptiness, low quarity\u3002
\n6.\u00a0Output<\/strong>: Point Queue Prompt\u3002<\/p>\n
\ndenoise\u00a00.6<\/strong>dpmpp_2m+20step+karras+CFG7.5. Effects: Attitudinal maps are maintained and the twilight is completely changed to Sabourpunk\u3002<\/p>\n
\ndenoise\u00a00.7 ~ 0.8<\/strong>(conservation line, new colours); recommended binary base model. The more specific the hint, the better the \"blue eyes, red skirts, blonde\" is\u3002<\/p>\n
\nnegative: blurry, low quality, damaged, scratch, noise
\ndenoise\u00a00.2 ~ 0.3<\/strong>(Minimum, high-level, old-fashioned photo features); better to be magnified with title 06\u3002<\/p>\n\n\n
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