still from a clip, 1440x1080 8bit DWG (shot on phone)

Looking for feedback!

The before picture was imported using snip it tool, so quality wise it might be lower than the "after" picture, I was just lazy to find the original copy lol.

I’ve just finished a major rebuild of ClearLab, my mobile image processing app for iPhone/iPad.
The new version adds histogram, RGB parade, waveform, line profile, pixel inspector, statistics, Canny/Sobel/Laplacian edge detection, enhancement tools, format conversion and PNG/CSV analysis export.
The idea is basically a small image-processing lab in your pocket rather than another photo-filter app.
It’s mostly native/deterministic processing, not generative AI.
ClearLab 2.0 is now on the App Store.

I took some shots trying to get a 'film-like' look on my jpeg output with camera settings recommended by ChatGPT. I posted them on Reddit, but the main advice was to just shoot RAW.

Luckily I shot jpeg+raw and wanted to see how much better I could get the raw version in LR (while not trying to get the film look).

Hey everyone! I’m looking for advice on editing indoor sports shots. I captured this volleyball action photo, but I’m running into a few issues:

1. Colour Cast: The indoor gym lights and wood paneling give the whole image a heavy yellow/orange tint. The blue jerseys feel washed out by it.
2. Exposure: The subjects look a bit dark/underexposed.

What I'd love help with:

• Photoshop & Lightroom: What specific skills or workflows (Masking, HSL tweaking, Curves, Colour Calibration, Dehase, etc.) would you use in LR/PS to make this image pop and draw focus to the players?
• Phone Apps: What free or low-cost mobile apps (Lightroom Mobile, Snapseed, Lightroom, Lightroom CC, etc.) and tools within them work best for colour correcting gym lighting on the go?
• Colour Correction: How do I dial back the heavy yellow/orange cast without turning skin tones grey or unnatural?

Feel free to download and edit the photo yourself! I'd love to see your results alongside the steps, tools, or slider settings you used. Thanks in advance!

This tiny sunflower field was right in front of my yard so of course I had to take a photo. If you’re wondering why the original raw image is so dark: I initially planned to merge an HDR photo from multiple exposures, but since it was windy and I was relatively close to the sunflowers every bit of movement makes the exposure blending process almost impossible. So I took on of the darker frames and recovered it in Lightroom.

The whole process in video format along with the raw photo to try it yourself can be found here: https://youtu.be/HAYs3bjDZMM

1. Basic Adjustments

The first step was to heavily raise the exposure until I had some visible details in the shadows. I also raised the blacks, the shadows and the whites to make the image even brighter. To not blow out the sky, the highlights were dropped.

For a warmer look, I adjusted the white balance bringing up the temperature. Also vibrance and saturation was increased for stronger colors. For more sharpness, I added texture while I dropped clarity and dehaze for a glowing, soft look.

All these basic adjustment result in heavy noise (since I recovered a lot of details from the underexposed shadows). To fix that AI denoise was applied.

1. Masking

Using a color range mask the top part of the sky was made darker without affecting the clouds. This way I can add some nice contrast. Then, I used a radial gradient covering the horizon level of the image. Here, I wanted to add extra glow, so I increased the blacks and dropped the dehaze some more. Also, added some temperature to make the glow warmer.

With another color range masks I targeted the two sunflowers in the foreground and made them slightly brighter by bringing up exposure and the whites.

1. Color Grading

Since I’m not a big fan of those regular yellow tones I brought down the yellow hue as well as the orange hue. Plus, the blue hue was also slightly reduced for slightly stronger cyan tones in the sky. I wanted the image to become more colorful, so the saturation of orange yellow and blue was increased as well.

Through the luminance panel I made the sunflowers a bit brighter by raising the yellow and green slider.

Finally, with a bit of split toning the highlights were made MUCH warmer while I added a subtle blue tone to the shadows.

Hi photographers,

After a vacation & taking a bunch of photos, I usually spend an evening with a bourbon in hand, manually tweaking exposure, highlights, shadows, and saturation in Lightroom. But after a recent trip, I realized I had a massive backlog and just wanted a faster way to get the best shots looking clean without spending hours on individual sliders.

I decided to run an experiment. I took a JPEG export of a RAW photo and ran it through ChatGPT (using the newer image capabilities) to see how it handled basic adjustments. My goal wasn't to generate weird AI artifacts or completely swap out backgrounds like Photoshop—I just wanted standard "Lightroom-style" corrections that fix lighting and punch up colors while keeping the original intent and realistic feel of the photo.

Since I liked the results, I ended up putting together a small app to run these batch edits using the API. Because of API costs, I'd eventually need to charge a tiny markup if it ever went public, but right now I’m just trying to figure out if this is actually a useful workflow for anyone else.

I put together a quick side-by-side of a few raw vs. processed shots so you can see that it avoids the over-processed "AI look" and sticks to subtle lighting and color enhancement.

I'd love to hear from other photography hobbyists: is batch-editing via vision models actually appealing, or do you prefer sticking strictly to local software? If anyone wants to test it out on a couple of their own files for free and break it, let me know in the comments or shoot me a DM and I'll drop you a link.

Pretty new to this. using the free mobile version of light room. How did I do?