docs: update readme. add docs to package

Clean up logging some more

.python-version

@@ -0,0 +1 @@
+imaginairy-3.10.6

LICENSE

@@ -1,5 +1,5 @@
-Copyright 2022 Bryce Drennan
-(for modifications on top of CompVis license)
+Copyright 2022 Bryce Drennan (and numerous other contributers as documented)
+(for modifications on top of CompVis code)
 
 The MIT License
 

README.md

@@ -31,20 +31,29 @@ Generating 🖼  : "portrait photo of a freckled woman" 512x512px seed:500686645
 
 ### Tiled Images
 ```bash
->> imagine "Art Nouveau mosaic" --tile
-🤖🧠 received 1 prompt(s) and will repeat them 1 times to create 1 images.
-Loading model onto mps backend...
-Generating 🖼  : "Art Nouveau mosaic" 512x512px seed:658241102 prompt-strength:7.5 steps:40 sampler-type:PLMS
-    PLMS Sampler: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 40/40 [00:31<00:00,  1.28it/s]
-    🖼  saved to: ./outputs/000058_658241102_PLMS40_PS7.5_Art_Nouveau_mosaic.jpg
+>> imagine  "gold coins" "a lush forest" "piles of old books" leaves --tile
+```
+
+<img src="assets/000066_801493266_PLMS40_PS7.5_gold_coins.jpg" height="128"><img src="assets/000066_801493266_PLMS40_PS7.5_gold_coins.jpg" height="128"><img src="assets/000066_801493266_PLMS40_PS7.5_gold_coins.jpg" height="128">
+<img src="assets/000118_597948545_PLMS40_PS7.5_a_lush_forest.jpg" height="128"><img src="assets/000118_597948545_PLMS40_PS7.5_a_lush_forest.jpg" height="128"><img src="assets/000118_597948545_PLMS40_PS7.5_a_lush_forest.jpg" height="128">
+<br>
+<img src="assets/000075_961095192_PLMS40_PS7.5_piles_of_old_books.jpg" height="128"><img src="assets/000075_961095192_PLMS40_PS7.5_piles_of_old_books.jpg" height="128"><img src="assets/000075_961095192_PLMS40_PS7.5_piles_of_old_books.jpg" height="128">
+<img src="assets/000040_527733581_PLMS40_PS7.5_leaves.jpg" height="128"><img src="assets/000040_527733581_PLMS40_PS7.5_leaves.jpg" height="128"><img src="assets/000040_527733581_PLMS40_PS7.5_leaves.jpg" height="128">
+
+### Image-to-Image
+```bash
+>> imagine "portrait of a smiling lady. oil painting" --init-image girl_with_a_pearl_earring.jpg
 ```
+<img src="tests/data/girl_with_a_pearl_earring.jpg" height="256"> =>
+<img src="assets/000105_33084057_DDIM40_PS7.5_portrait_of_a_smiling_lady._oil_painting._.jpg" height="256"> 
+
 
-<img src="assets/000057_802839261_PLMS40_PS7.5_Art_Nouveau_mosaic._ornate,_highly_detailed,_sharp_focus.jpg" width="256" height="256"><img src="assets/000057_802839261_PLMS40_PS7.5_Art_Nouveau_mosaic._ornate,_highly_detailed,_sharp_focus.jpg" width="256" height="256">
 ## Features
  
  - It makes images from text descriptions! 🎉
  - Generate images either in code or from command line.
- - It just works. Proper requirements installed, model weights automatically downloaded. No huggingface account needed. (if you have the right hardware... and aren't on windows)
+ - It just works. Proper requirements are installed. model weights are automatically downloaded. No huggingface account needed. 
+    (if you have the right hardware... and aren't on windows)
  - Noisy logs are gone (which was surprisingly hard to accomplish)
  - WeightedPrompts let you smash together separate prompts (cat-dog)
  - Tile Mode creates tileable images
@@ -73,18 +82,15 @@ imagine_image_files(prompts, outdir="./my-art")
 
 ```
 
-# Requirements
-
-- Computer with CUDA supported graphics card. ~10 gb video ram
-OR
-- Apple M1 computer
+## Requirements
+- ~10 gb space for models to download
+- A decent computer with either a CUDA supported graphics card or M1 processor.
 
-# Improvements from CompVis
+## Improvements from CompVis
  - img2img actually does # of steps you specify
  - performance optimizations
- - 
 
-# Models Used
+## Models Used
  - CLIP - https://openai.com/blog/clip/
  - LDM - Latent Diffusion
  - Stable Diffusion 
@@ -92,10 +98,13 @@ OR
    - https://huggingface.co/CompVis/stable-diffusion-v1-4
    - https://laion.ai/blog/laion-5b/
 
-# Todo
- - performance optimizations 
-   - https://github.com/huggingface/diffusers/blob/main/docs/source/optimization/fp16.mdx
-   - https://github.com/neonsecret/stable-diffusion
+## Not Supported
+ - a web interface. this is a python library
+
+## Todo
+ - performance optimizations
+   - https://github.com/neonsecret/stable-diffusion  https://github.com/CompVis/stable-diffusion/pull/177
+   - ✅ https://github.com/huggingface/diffusers/blob/main/docs/source/optimization/fp16.mdx
    - ✅ https://github.com/CompVis/stable-diffusion/compare/main...Doggettx:stable-diffusion:autocast-improvements#
    - ✅ https://www.reddit.com/r/StableDiffusion/comments/xalaws/test_update_for_less_memory_usage_and_higher/
  - deploy to pypi
@@ -106,14 +115,14 @@ OR
  - remove yaml config
  - delete more unused code
  - Interface improvements
-   - init-image at command line
-   - prompt expansion?
-   - webserver interface (low priority, this is a library)
+   - ✅ init-image at command line
+   - prompt expansion
  - Image Generation Features
    - upscaling
      - https://github.com/lowfuel/progrock-stable
    - face improvements
-     - codeformer
+     - gfpgan - https://github.com/TencentARC/GFPGAN
+     - codeformer - https://github.com/sczhou/CodeFormer
    - image describe feature - https://replicate.com/methexis-inc/img2prompt
    - outpainting
    - inpainting
@@ -135,5 +144,3 @@ OR
      - https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_textual_inversion_training.ipynb#scrollTo=50JuJUM8EG1h
    - zooming videos? a la disco diffusion
    - fix saturation at high CFG https://www.reddit.com/r/StableDiffusion/comments/xalo78/fixing_excessive_contrastsaturation_resulting/
-
- 

imaginairy/cmds.py

@@ -57,7 +57,8 @@ def configure_logging(level="INFO"):
 )
 @click.option(
     "--init-image-strength",
-    default=0.3,
+    default=0.6,
+    show_default=True,
     help="Starting image.",
 )
 @click.option("--outdir", default="./outputs", help="where to write results to")
@@ -143,6 +144,8 @@ def imagine_cmd(
     logger.info(
         f"🤖🧠 received {len(prompt_texts)} prompt(s) and will repeat them {repeats} times to create {total_image_count} images."
     )
+    if init_image and sampler_type != "DDIM":
+        sampler_type = "DDIM"
 
     prompts = []
     load_model(tile_mode=tile)

imaginairy/modules/diffusion/ddim.py

@@ -128,7 +128,7 @@ class DDIMSampler:
         # sampling
         C, H, W = shape
         size = (batch_size, C, H, W)
-        logger.info(f"Data shape for DDIM sampling is {size}, eta {eta}")
+        logger.debug(f"Data shape for DDIM sampling is {size}, eta {eta}")
 
         samples, intermediates = self.ddim_sampling(
             conditioning,
@@ -351,7 +351,7 @@ class DDIMSampler:
 
         time_range = np.flip(timesteps)
         total_steps = timesteps.shape[0]
-        logger.info(f"Running DDIM Sampling with {total_steps} timesteps")
+        logger.debug(f"Running DDIM Sampling with {total_steps} timesteps")
 
         iterator = tqdm(time_range, desc="Decoding image", total=total_steps)
         x_dec = x_latent

setup.py

@@ -1,9 +1,16 @@
 from setuptools import find_packages, setup
 
+with open("README.md", "r", encoding="utf-8") as f:
+    readme = f.read()
+
 setup(
-    name="imaginairy",
-    version="0.0.1",
-    description="AI imagined images.",
+    name="imaginAIry",
+    author="Bryce Drennan",
+    author_email="b r y p y d o t io",
+    version="0.7.0",
+    description="AI imagined images. Pythonic generation of stable diffusion images.",
+    long_description=readme,
+    long_description_content_type="text/markdown",
     packages=find_packages(include=("imaginairy", "imaginairy.*")),
     entry_points={
         "console_scripts": ["imagine=imaginairy.cmd_wrap:imagine_cmd"],