…
. Probably they want that format. We’ll need to produce paragraphs with that wrapper. We need to embed the facts: Actionable Framework, Checklist for Color Grading Automation, Checklist for Exposure Automation, Example Setup in Aftershoot (or similar), Example, Framework: The 3‑Step Skin Match, How to Automate It, How to automate it (maybe duplicate?), Preset Name: “Corporate Clean V1”, Real-World Example, Skin Tone as a Grey Card, Workflow Integration with bullet points (list items). We need to convey these facts. Word count 450-500 words. Let’s aim for ~470 words. We need to count words. Let’s draft then count. We’ll produce HTML with headings: maybe h2 for sections. We’ll use…
and paragraphs accordingly. Let’s draft content. Title line: “Title: Automating Exposure and Color Corrections: AI Retouching Basics for Headshot and Portrait Freelancers” Make sure includes “AI” and “ai”. Title includes “AI” and also “ai”? It says include “AI” and “ai”. Could have both uppercase and lowercase. Title: “Automating Exposure and Color Corrections: AI Retouching Basics for Headshot and Portrait Freelancers” includes AI but not lowercase “ai”. Could add “ai” somewhere else in title like “AI/ai”. Maybe “Automating Exposure and Color Corrections: AI/ai Retouching Basics for Headshot and Portrait Freelancers”. That includes both. Now content. We need to count words. Let’s write then count manually. I’ll write content with HTML wrappers. Start after title line and blank line. We’ll produce:…
Let’s draft. I’ll write sentences then count. Draft:Freelance portrait photographers spend hours sorting, correcting, and delivering images; AI automation can cut that time in half while keeping consistent quality.
Start with an actionable framework: import raw files into an AI‑assisted culling tool, let the software flag keepers based on focus, expression, and exposure, then move the selected shots to a retouching preset.
Checklist for Color Grading Automation
• Define a neutral skin tone reference using a grey card or known skin patch.
• Set global correction to remove any cast (e.g., blue window light).
• Adjust skin saturation –8 to keep tones natural.
• Apply a slight lift to shadows (+10) for depth in hair and clothing.
• Pull highlights –10 to –15 to retain detail on forehead and cheek shine.
• Add contrast +8 and exposure +0.10 for a balanced look.
• Set blacks –5 to deepen hair without crushing detail.
Checklist for Exposure Automation
• Use the AI’s exposure analysis to target a middle‑gray value.
• Apply the global exposure shift (+0.10) as a baseline.
• Fine‑tune with local dodge/burn only if the AI flags over‑ or under‑exposed spots.
• Lock the exposure layer before moving to color grading to avoid drift.
Example Setup in Aftershoot (or Similar)
1. Create a new AI preset called “Corporate Clean V1”.
2. Input the checklist values: Blacks –5, Contrast +8, Exposure +0.10, Global correction neutral, Highlights –12 (average of –10 to –15), Shadows +10, Skin Saturation –8.
3. Enable the “Skin Tone as Grey Card” option so the AI uses the detected skin patch to set white balance.
4. Save the preset and apply it to all culled headshots with one click.
Framework: The 3‑Step Skin Match
Step 1: Detect skin region and compute its average RGB.
Step 2: Compare to a reference grey card value and calculate the needed offset.
Step 3: Apply that offset as a global color correction, then lock the setting for the rest of the batch.
How to Automate It
In Aftershoot, enable the “Auto Skin Match” module, feed it the reference grey card shot, and let the AI generate the correction layer.
Export the correction as an XMP preset and sync it with Lightroom or Capture One for final tweaks.
For a comprehensive guide with detailed workflows, templates, and additional strategies, see my e-book: AI for Freelance Portrait Photographers: How to Automate Photo Culling, Basic Retouching, and Gallery Delivery.
Now we need to count words. We’ll count words in the content (excluding the title line? Probably include title line words as well? Usually word count includes everything. Safer to count everything after “Title:” line as well. We’ll count all. Let’s extract text. Title line: “Title: Automating Exposure and Color Corrections: AI/ai Retouching Basics for Headshot and Portrait Freelancers” Now paragraphs. I’ll copy text and count manually. I’ll create a list. Title words: Title: (maybe counts as “Title:” as one word? Usually “Title:” counts as one token but we treat as word “Title:”? Safer to count “Title:” as one word. Then “Automating”(2) “Exposure”(3) “and”(4) “Color”(5) “Corrections:”(6) “AI/ai”(7) “Retouching”(8) “Basics”(9) “for”(10) “Headshot”(11) “and”(12) “Portrait”(13) “Freelancers”(14) So title: 14 words. Now paragraph 1: “Freelance portrait photographers spend hours sorting, correcting, and delivering images; AI automation can cut that time in half while keeping consistent quality.” Count words: Freelance1 portrait2 photographers3 spend4 hours5 sorting,6 correcting,7 and8 delivering9 images;10 AI11 automation12 can13 cut14 that15 time16 in17 half18 while19 keeping20 consistent21 quality22. 22 words. Paragraph 2: “Start with an actionable framework: import raw files into an AI‑assisted culling tool, let the software flag keepers based on focus, expression, and exposure, then move the selected shots to a retouching preset.” Count: Start1 with2 an3 actionable4 framework:5 import6 raw7 files8 into9 an10 AI‑assisted11 culling12 tool,13 let14 the15 software16 flag17 keepers18 based19 on20 focus,21 expression,22 and23 exposure,24 then25 move26 the27 selected28 shots29 to30 a31 retouching32 preset33. 33 words. Heading 2: “Checklist for Color Grading Automation” words: Checklist1 for2 Color3 Grading4 Automation5 =>5 Paragraph after heading (first bullet): “• Define a neutral skin tone reference using a grey card or known skin patch.” We need to count words ignoring bullet symbol. Words: Define1 a2 neutral3 skin4 tone5 reference6 using7 a8 grey9 card10 or11 known12 skin13 patch14. =>14 Next paragraph: “• Set global correction to remove any cast (e.g., blue window light).” Words: Set1 global2 correction3 to4 remove5 any6 cast7 (e.g.,8 blue9 window10 light).11 =>11 Next: “• Adjust skin saturation –8 to keep tones natural.” Words: Adjust1 skin2 saturation3 –84 to5 keep6 tones7 natural8. =>8 Next: “• Apply a slight lift to shadows (+10) for depth in hair and clothing.” Words: Apply1 a2 slight3 lift4 to5 shadows6 (+10)7 for8 depth9 in10 hair11 and12 clothing13. =>13 Next: “• Pull highlights –10 to –15 to retain detail on forehead and cheek shine.” Words: Pull1 highlights2 –103 to4 –155 to6 retain7 detail8 on9 forehead10 and11 cheek12 shine13. =>13 Next: “• Add contrast +8 and exposure +0.10 for a balanced look.” Words: Add1 contrast2 +83 and4 exposure5 +0.106 for7 a8 balanced9 look10. =>10 Next: “• Set blacks –5 to deepen hair without crushing detail.” Words: Set1 blacks2 –53 to4 deepen5 hair6 without7 crushing8 detail9. =>9 Now heading: “Checklist for Exposure Automation” words: Checklist1 for2 Exposure3 Automation4 =>4 Paragraph after heading: “• Use the AI’s exposure analysis to target a middle‑gray value.” Words: Use1 the2 AI’s3 exposure4 analysis5 to6 target7 a8 middle‑gray9 value10. =>10 Next: “• Apply the global exposure shift (+0.10) as a baseline.” Words: Apply1 the2 global3 exposure4 shift5 (+0.10)6 as7 a8 baseline9. =>9 Next: “• Fine‑tune with local dodge/burn only if the AI flags over‑ or under‑exposed spots.” Words: Fine‑tune1 with2 local3 dodge/burn4 only5 if6 the7 AI8 flags9 over‑10 or11 under‑exposed12 spots13. =>13 Next: “• Lock the exposure layer before moving to color grading to avoid drift.” Words: Lock1 the2 exposure3 layer4 before5 moving6 to7 color8 grading9 to10 avoid11 drift12. =>12 Heading: “Example Setup in Aftershoot (or Similar)” words: Example1 Setup2 in3 Aftershoot4 (or5 Similar)6 =>6 Paragraph after heading: “