more updates to many docs, including:

- better readability in dark mode since color change - better looking changelog - fix images which where not loading - also center most of the images - fix some syntax errors like - headlines ending with a colon - codeblocks with wrong fences - codeblocks without shell - update conda prompts from ldm to invokeai - ....
incompleteml · Oct 12, 2022 · 1c687d6 · 1c687d6
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diff --git a/docs/CHANGELOG.md b/docs/CHANGELOG.md
@@ -4,7 +4,7 @@ title: Changelog
 
 # :octicons-log-16: **Changelog**
 
-- v2.0.0 (9 October 2022)
+## v2.0.0 <small>(9 October 2022)</small>
 
   - `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
     for backward compatibility.
@@ -31,7 +31,7 @@ title: Changelog
   - Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
     configure. To switch away from auto use the new flag like `--precision=float32`.
 
-- v1.14 (11 September 2022)
+## v1.14 <small>(11 September 2022)</small>
 
   - Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
   - Full support for Apple hardware with M1 or M2 chips.
@@ -41,7 +41,7 @@ title: Changelog
   - Improved web server GUI.
   - Lots of code and documentation cleanups.
 
-- v1.13 (3 September 2022
+## v1.13 <small>(3 September 2022)</small>
 
   - Support image variations (see [VARIATIONS](features/VARIATIONS.md)
     ([Kevin Gibbons](https://github.com/bakkot) and many contributors and reviewers)
@@ -61,7 +61,7 @@ title: Changelog
 
 ---
 
-## v1.12 (28 August 2022)
+## v1.12 <small>(28 August 2022)</small>
 
 - Improved file handling, including ability to read prompts from standard input.
   (kudos to [Yunsaki](https://github.com/yunsaki)
@@ -75,7 +75,7 @@ title: Changelog
 
 ---
 
-## v1.11 (26 August 2022)
+## v1.11 <small>(26 August 2022)</small>
 
 - NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to [Oceanswave](https://github.com/Oceanswave)
 - You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc.
@@ -88,13 +88,13 @@ title: Changelog
 
 ---
 
-## v1.10 (25 August 2022)
+## v1.10 <small>(25 August 2022)</small>
 
 - A barebones but fully functional interactive web server for online generation of txt2img and img2img.
 
 ---
 
-## v1.09 (24 August 2022)
+## v1.09 <small>(24 August 2022)</small>
 
 - A new -v option allows you to generate multiple variants of an initial image
   in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave). [
@@ -104,7 +104,7 @@ title: Changelog
 
 ---
 
-## v1.08 (24 August 2022)
+## v1.08 <small>(24 August 2022)</small>
 
 - Escape single quotes on the invoke> command before trying to parse. This avoids
   parse errors.
@@ -115,22 +115,22 @@ title: Changelog
 
 ---
 
-## v1.07 (23 August 2022)
+## v1.07 <small>(23 August 2022)</small>
 
 - Image filenames will now never fill gaps in the sequence, but will be assigned the
   next higher name in the chosen directory. This ensures that the alphabetic and chronological
   sort orders are the same.
 
 ---
 
-## v1.06 (23 August 2022)
+## v1.06 <small>(23 August 2022)</small>
 
 - Added weighted prompt support contributed by [xraxra](https://github.com/xraxra)
 - Example of using weighted prompts to tweak a demonic figure contributed by [bmaltais](https://github.com/bmaltais)
 
 ---
 
-## v1.05 (22 August 2022 - after the drop)
+## v1.05 <small>(22 August 2022 - after the drop)</small>
 
 - Filenames now use the following formats:
   000010.95183149.png -- Two files produced by the same command (e.g. -n2),
@@ -148,22 +148,22 @@ title: Changelog
 
 ---
 
-## v1.04 (22 August 2022 - after the drop)
+## v1.04 <small>(22 August 2022 - after the drop)</small>
 
 - Updated README to reflect installation of the released weights.
 - Suppressed very noisy and inconsequential warning when loading the frozen CLIP
   tokenizer.
 
 ---
 
-## v1.03 (22 August 2022)
+## v1.03 <small>(22 August 2022)</small>
 
 - The original txt2img and img2img scripts from the CompViz repository have been moved into
   a subfolder named "orig_scripts", to reduce confusion.
 
 ---
 
-## v1.02 (21 August 2022)
+## v1.02 <small>(21 August 2022)</small>
 
 - A copy of the prompt and all of its switches and options is now stored in the corresponding
   image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py,
@@ -172,7 +172,7 @@ title: Changelog
 
 ---
 
-## v1.01 (21 August 2022)
+## v1.01 <small>(21 August 2022)</small>
 
 - added k_lms sampling.
   **Please run "conda env update" to load the k_lms dependencies!!**

diff --git a/docs/features/CLI.md b/docs/features/CLI.md
@@ -34,7 +34,7 @@ The script is confirmed to work on Linux, Windows and Mac systems.
     currently rudimentary, but a much better replacement is on its way.
 
 ```bash
-(ldm) ~/stable-diffusion$ python3 ./scripts/invoke.py
+(invokeai) ~/stable-diffusion$ python3 ./scripts/invoke.py
 * Initializing, be patient...
 Loading model from models/ldm/text2img-large/model.ckpt
 (...more initialization messages...)
@@ -51,7 +51,7 @@ invoke> "there's a fly in my soup" -n6 -g
 invoke> q
 
 # this shows how to retrieve the prompt stored in the saved image's metadata
-(ldm) ~/stable-diffusion$ python ./scripts/images2prompt.py outputs/img_samples/*.png
+(invokeai) ~/stable-diffusion$ python ./scripts/images2prompt.py outputs/img_samples/*.png
 00009.png: "ashley judd riding a camel" -s150 -S 416354203
 00010.png: "ashley judd riding a camel" -s150 -S 1362479620
 00011.png: "there's a fly in my soup" -n6 -g -S 2685670268

diff --git a/docs/features/INPAINTING.md b/docs/features/INPAINTING.md
@@ -50,28 +50,28 @@ We are hoping to get rid of the need for this workaround in an upcoming release.
 
 1. Open image in Photoshop
 
-    ![step1](../assets/step1.png)
+    <div align="center" markdown>![step1](../assets/step1.png)</div>
 
 2. Use any of the selection tools (Marquee, Lasso, or Wand) to select the area you desire to inpaint.
 
-    ![step2](../assets/step2.png)
+    <div align="center" markdown>![step2](../assets/step2.png)</div>
 
 3. Because we'll be applying a mask over the area we want to preserve, you should now select the inverse by using the ++shift+ctrl+i++ shortcut, or right clicking and using the "Select Inverse" option.
 
 4. You'll now create a mask by selecting the image layer, and Masking the selection. Make sure that you don't delete any of the undrlying image, or your inpainting results will be dramatically impacted.
 
-    ![step4](../assets/step4.png)
+    <div align="center" markdown>![step4](../assets/step4.png)</div>
 
 5. Make sure to hide any background layers that are present. You should see the mask applied to your image layer, and the image on your canvas should display the checkered background.
 
-    ![step5](../assets/step5.png)
+    <div align="center" markdown>![step5](../assets/step5.png)</div>
 
 6. Save the image as a transparent PNG by using `File`-->`Save a Copy` from the menu bar, or by using the keyboard shortcut ++alt+ctrl+s++
 
-    ![step6](../assets/step6.png)
+    <div align="center" markdown>![step6](../assets/step6.png)</div>
 
 7. After following the inpainting instructions above (either through the CLI or the Web UI), marvel at your newfound ability to selectively invoke. Lookin' good!
 
-    ![step7](../assets/step7.png)
+    <div align="center" markdown>![step7](../assets/step7.png)</div>
 
 8. In the export dialogue, Make sure the "Save colour values from transparent pixels" checkbox is selected.  
diff --git a/docs/features/OTHER.md b/docs/features/OTHER.md
@@ -6,11 +6,13 @@ title: Others
 
 ## **Google Colab**
 
-Stable Diffusion AI Notebook: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lstein/stable-diffusion/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg){ align="right" }](https://colab.research.google.com/github/lstein/stable-diffusion/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
 
 Open and follow instructions to use an isolated environment running Dream.
 
-Output Example: ![Colab Notebook](../assets/colab_notebook.png)
+Output Example:
+
+![Colab Notebook](../assets/colab_notebook.png)
 
 ---
 
@@ -29,12 +31,12 @@ invoke> "pond garden with lotus by claude monet" --seamless -s100 -n4
 ## **Shortcuts: Reusing Seeds**
 
 Since it is so common to reuse seeds while refining a prompt, there is now a shortcut as of version
-1.11. Provide a `**-S**` (or `**--seed**`) switch of `-1` to use the seed of the most recent image
-generated. If you produced multiple images with the `**-n**` switch, then you can go back further
-using -2, -3, etc. up to the first image generated by the previous command. Sorry, but you can't go
+1.11. Provide a `-S` (or `--seed`) switch of `-1` to use the seed of the most recent image
+generated. If you produced multiple images with the `-n` switch, then you can go back further
+using `-2`, `-3`, etc. up to the first image generated by the previous command. Sorry, but you can't go
 back further than one command.
 
-Here's an example of using this to do a quick refinement. It also illustrates using the new `**-G**`
+Here's an example of using this to do a quick refinement. It also illustrates using the new `-G`
 switch to turn on upscaling and face enhancement (see previous section):
 
 ```bash
@@ -54,7 +56,7 @@ outputs/img-samples/000040.3498014304.png: "a cute child playing hopscotch" -G1.
 ## **Weighted Prompts**
 
 You may weight different sections of the prompt to tell the sampler to attach different levels of
-priority to them, by adding `:(number)` to the end of the section you wish to up- or downweight. For
+priority to them, by adding `:<percent>` to the end of the section you wish to up- or downweight. For
 example consider this prompt:
 
 ```bash
@@ -122,7 +124,7 @@ internet. In the following runs, it will load up the cached versions of the requ
 `.cache` directory of the system.
 
 ```bash
-(ldm) ~/stable-diffusion$ python3 ./scripts/preload_models.py
+(invokeai) ~/stable-diffusion$ python3 ./scripts/preload_models.py
 preloading bert tokenizer...
 Downloading: 100%|██████████████████████████████████| 28.0/28.0 [00:00<00:00, 49.3kB/s]
 Downloading: 100%|██████████████████████████████████| 226k/226k [00:00<00:00, 2.79MB/s]

diff --git a/docs/features/OUTPAINTING.md b/docs/features/OUTPAINTING.md
@@ -25,14 +25,16 @@ implementations.
 
 Consider this image:
 
+<div align="center" markdown>
 ![curly_woman](../assets/outpainting/curly.png)
+</div>
 
 Pretty nice, but it's annoying that the top of her head is cut
 off. She's also a bit off center. Let's fix that!
 
-~~~~
+```bash
 invoke> !fix images/curly.png --outcrop top 64 right 64
-~~~~
+```
 
 This is saying to apply the `outcrop` extension by extending the top
 of the image by 64 pixels, and the right of the image by the same
@@ -42,7 +44,9 @@ specify any number of pixels to extend. You can also abbreviate
 
 The result looks like this:
 
+<div align="center" markdown>
 ![curly_woman_outcrop](../assets/outpainting/curly-outcrop.png)
+</div>
 
 The new image is actually slightly larger than the original (576x576,
 because 64 pixels were added to the top and right sides.)
@@ -66,33 +70,36 @@ The `outpaint` extension does the same thing, but with subtle
 differences. Starting with the same image, here is how we would add an
 additional 64 pixels to the top of the image:
 
-~~~
+```bash
 invoke> !fix images/curly.png --out_direction top 64
-~~~
+```
 
 (you can abbreviate `--out_direction` as `-D`.
 
 The result is shown here:
 
+<div align="center" markdown>
 ![curly_woman_outpaint](../assets/outpainting/curly-outpaint.png)
+</div>
 
 Although the effect is similar, there are significant differences from
 outcropping:
 
-1. You can only specify one direction to extend at a time.
-2. The image is **not** resized. Instead, the image is shifted by the specified
+- You can only specify one direction to extend at a time.
+- The image is **not** resized. Instead, the image is shifted by the specified
 number of pixels. If you look carefully, you'll see that less of the lady's
 torso is visible in the image.
-3. Because the image dimensions remain the same, there's no rounding
+- Because the image dimensions remain the same, there's no rounding
 to multiples of 64.
-4. Attempting to outpaint larger areas will frequently give rise to ugly
+- Attempting to outpaint larger areas will frequently give rise to ugly
    ghosting effects.
-5. For best results, try increasing the step number.
-6. If you don't specify a pixel value in -D, it will default to half
+- For best results, try increasing the step number.
+- If you don't specify a pixel value in `-D`, it will default to half
    of the whole image, which is likely not what you want.
 
-Neither `outpaint` nor `outcrop` are perfect, but we continue to tune
-and improve them. If one doesn't work, try the other. You may also
-wish to experiment with other `img2img` arguments, such as `-C`, `-f`
-and `-s`.
+!!! tip
 
+    Neither `outpaint` nor `outcrop` are perfect, but we continue to tune
+    and improve them. If one doesn't work, try the other. You may also
+    wish to experiment with other `img2img` arguments, such as `-C`, `-f`
+    and `-s`.
diff --git a/docs/features/POSTPROCESS.md b/docs/features/POSTPROCESS.md
@@ -34,13 +34,13 @@ work. These are loaded when you run `scripts/preload_models.py`. If
 GFPAN is failing with an error, please run the following from the
 InvokeAI directory:
 
-~~~~
+```bash
 python scripts/preload_models.py
-~~~~
+```
 
 If you do not run this script in advance, the GFPGAN module will attempt
 to download the models files the first time you try to perform facial
-reconstruction. 
+reconstruction.
 
 Alternatively, if you have GFPGAN installed elsewhere, or if you are
 using an earlier version of this package which asked you to install
@@ -89,13 +89,13 @@ too.
 ### Example Usage
 
 ```bash
-invoke> superman dancing with a panda bear -U 2 0.6 -G 0.4
+invoke> "superman dancing with a panda bear" -U 2 0.6 -G 0.4
 ```
 
 This also works with img2img:
 
 ```bash
-invoke> a man wearing a pineapple hat -I path/to/your/file.png -U 2 0.5 -G 0.6
+invoke> "a man wearing a pineapple hat" -I path/to/your/file.png -U 2 0.5 -G 0.6
 ```
 
 !!! note
@@ -129,14 +129,14 @@ You can use `-ft` prompt argument to swap between CodeFormer and the
 default GFPGAN. The above mentioned `-G` prompt argument will allow
 you to control the strength of the restoration effect.
 
-### Usage:
+### Usage
 
 The following command will perform face restoration with CodeFormer instead of
 the default gfpgan.
 
 `<prompt> -G 0.8 -ft codeformer`
 
-### Other Options:
+### Other Options
 
 - `-cf` - cf or CodeFormer Fidelity takes values between `0` and `1`. 0 produces
   high quality results but low accuracy and 1 produces lower quality results but
@@ -162,15 +162,15 @@ previously-generated file. Just use the syntax `!fix path/to/file.png
 2X for a file named `./outputs/img-samples/000044.2945021133.png`,
 just run:
 
-```
+```bash
 invoke> !fix ./outputs/img-samples/000044.2945021133.png -G 0.8 -U 2
 ```
 
 A new file named `000044.2945021133.fixed.png` will be created in the output
 directory. Note that the `!fix` command does not replace the original file,
 unlike the behavior at generate time.
 
-### Disabling:
+### Disabling
 
 If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries,
 you can disable them on the invoke.py command line with the `--no_restore` and