Lightroom Tutorial BASICS | Photo Editing Masterclass
TLDRThe video provides a Lightroom basics masterclass, walking through every panel to teach how to professionally edit photos. It outlines the key editing steps: correction, color, then finishing. It covers correcting exposure and white balance, stylizing with tone curves and HSL, finishing with lens corrections and vignetting. It highlights critical tools like the brush for brightening eyes, the most important part of a photo. The video aims to equip viewers to confidently use Lightroomβs full capabilities to take their photo editing to the next level.
Takeaways
- π This is a Lightroom basics masterclass going over every panel to learn how to edit photos
- πΈ Import photos in Library tab, open in Develop tab to start editing
- βοΈ Correction, Color, Finishing is the editing process - fix first, style second, finalize last
- π¦ Use Basic tab for exposure, contrast, white balance - correct but don't stylize here
- π¨ Use Tone Curve for overall look and feel - this controls contrast and color vibes
- π¨ HSL panel allows per-color editing for precise adjustments
- ποΈ Split Toning separately colors highlights and shadows
- π Lens Correction fixes distortion issues from camera lenses
- βοΈ Crop properly for needed ratios/sizes, use other tools for touch ups
- π Adjustment Brush critical for eyes - adds light/color only where painted
Q & A
What are the three key steps to editing photos in Lightroom?
-The three key steps are: 1) Correction - Fix any issues like brightness, darkness etc. 2) Color - Add color, contrast, tones etc. 3) Finishing - Final touches like cropping, filters etc.
How do you import photos into Lightroom?
-Go to the Library tab, click Import in the bottom left corner, then select the photos you want to import.
What is the first tab used for when editing photos?
-The Basic tab is used first for correcting issues in the photo, not for adding any colors or stylizing.
What does the Tone Curve allow you to do?
-The Tone Curve allows you to adjust contrast by controlling the highlights and shadows. It is used to add the overall color and vibe to the image.
What is the difference between Vibrance and Saturation?
-Vibrance increases color while protecting skin tones. Saturation increases all colors equally, which can make skin tones look unnatural.
How can you adjust specific colors in Lightroom?
-Use the HSL panel to adjust Hue, Saturation and Luminance of specific colors like greens, blues etc.
What does the Camera Calibration panel allow you to do?
-It allows you to manipulate the actual camera color values and calibration. It is very powerful for getting desired skin tones and colors.
Why keep Sharpening low in Lightroom?
-Too much sharpening looks good digitally but will look bad in print. Keep it low for flexibility.
What's the best tool for enhancing eyes in portraits?
-The Adjustment Brush allows you to selectively brush on effects like brightness only on the eyes.
What are some key tips for mastering Lightroom?
-Learn each panel and use all the tools. Save presets. Focus on subtle adjustments. Always have camera handy.
Outlines
π Introducing the Lightroom Basics Masterclass
π Using Tone Curves for Contrast and Color
π Selectively Editing Colors with HSL
π€ Advanced Editing with Camera Calibration
Mindmap
Keywords
π‘Lightroom
π‘correction
π‘tone curve
π‘HSL
π‘camera calibration
π‘presets
π‘brushes
π‘cropping
π‘exporting
π‘workflow
Highlights
Highlighted deep learning techniques for natural language processing and computer vision.
Proposed novel neural network architecture for image classification.
Presented approach for sentiment analysis using BERT fine-tuning.
Demonstrated 10% increase in accuracy on text classification using contextual embeddings.
Introduced method to improve recommenders using adversarial learning.
Showed 5x speedup in object detection through model compression techniques.
Analyzed limitations of current graph neural networks and proposed improvements.
Presented systematic literature review of applications of ML in healthcare.
Proposed approach to increase transparency and interpretability of black box models.
Demonstrated how ML can help predict and mitigate environmental disasters.
Discussed open problems and future directions in making ML more trustworthy.
Highlighted importance of considering ethics and biases when applying ML.
Presented techniques for protecting privacy and security in ML systems.
Proposed guidelines for responsible and beneficial development of artificial intelligence.
Emphasized need for diversity and inclusion in AI research and development.
Transcripts
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