feature: negative prompting

- feature: negative prompting.  `--negative-prompt` or `ImaginePrompt(..., negative_prompt="ugly, deformed, extra arms, etc")`
- feature: a default negative prompt is added to all generations. Images in SD-2.0 don't look bad anymore. Images in 1.5 look improved as well.

README.md

@@ -230,6 +230,10 @@ docker run -it --gpus all -v $HOME/.cache/huggingface:/root/.cache/huggingface -
 [Example Colab](https://colab.research.google.com/drive/1rOvQNs0Cmn_yU1bKWjCOHzGVDgZkaTtO?usp=sharing)
 
 ## ChangeLog
+**7.0.0**
+- feature: negative prompting.  `--negative-prompt` or `ImaginePrompt(..., negative_prompt="ugly, deformed, extra arms, etc")`
+- feature: a default negative prompt is added to all generations. Images in SD-2.0 don't look bad anymore. Images in 1.5 look improved as well.
+
 **6.1.2**
 - fix: add back in memory-efficient algorithms
 

imaginairy/api.py

@@ -147,20 +147,16 @@ def imagine(
                 seed_everything(prompt.seed)
                 model.tile_mode(prompt.tile_mode)
                 with lc.timing("conditioning"):
-                    neutral_conditioning = None
-                    if prompt.prompt_strength != 1.0:
-                        neutral_conditioning = model.get_learned_conditioning(
-                            batch_size * [""]
-                        )
-                        log_conditioning(neutral_conditioning, "neutral conditioning")
+                    # need to expand if doing batches
+                    neutral_conditioning = _prompts_to_embeddings(
+                        prompt.negative_prompt, model
+                    )
+                    log_conditioning(neutral_conditioning, "neutral conditioning")
                     if prompt.conditioning is not None:
                         positive_conditioning = prompt.conditioning
                     else:
-                        total_weight = sum(wp.weight for wp in prompt.prompts)
-                        positive_conditioning = sum(
-                            model.get_learned_conditioning(wp.text)
-                            * (wp.weight / total_weight)
-                            for wp in prompt.prompts
+                        positive_conditioning = _prompts_to_embeddings(
+                            prompt.prompts, model
                         )
                     log_conditioning(positive_conditioning, "positive conditioning")
 
@@ -405,5 +401,14 @@ def imagine(
                     yield result
 
 
+def _prompts_to_embeddings(prompts, model):
+    total_weight = sum(wp.weight for wp in prompts)
+    conditioning = sum(
+        model.get_learned_conditioning(wp.text) * (wp.weight / total_weight)
+        for wp in prompts
+    )
+    return conditioning
+
+
 def prompt_normalized(prompt):
     return re.sub(r"[^a-zA-Z0-9.,\[\]-]+", "_", prompt)[:130]

imaginairy/cmds.py

@@ -16,6 +16,12 @@ logger = logging.getLogger(__name__)
 
 @click.command()
 @click.argument("prompt_texts", nargs=-1)
+@click.option(
+    "--negative-prompt",
+    default=config.DEFAULT_NEGATIVE_PROMPT,
+    show_default=True,
+    help="Negative prompt. Things to try and exclude from images. Same negative prompt will be used for all images.",
+)
 @click.option(
     "--prompt-strength",
     default=7.5,
@@ -177,6 +183,7 @@ logger = logging.getLogger(__name__)
 def imagine_cmd(
     ctx,
     prompt_texts,
+    negative_prompt,
     prompt_strength,
     init_image,
     init_image_strength,
@@ -235,6 +242,7 @@ def imagine_cmd(
             prompt_iterator = prompt_expanding_iterators[prompt_text]
             prompt = ImaginePrompt(
                 next(prompt_iterator),
+                negative_prompt=negative_prompt,
                 prompt_strength=prompt_strength,
                 init_image=init_image,
                 init_image_strength=init_image_strength,

imaginairy/config.py

@@ -3,6 +3,15 @@ from dataclasses import dataclass
 DEFAULT_MODEL = "SD-1.5"
 DEFAULT_SAMPLER = "k_dpmpp_2m"
 
+DEFAULT_NEGATIVE_PROMPT = (
+    "Ugly, duplication, duplicates, mutilation, deformed, mutilated, mutation, twisted body, disfigured, bad anatomy, "
+    "out of frame, extra fingers, mutated hands, "
+    "poorly drawn hands, extra limbs, malformed limbs, missing arms, extra arms, missing legs, extra legs, mutated hands, "
+    "extra hands, fused fingers, missing fingers, extra fingers, long neck, small head, closed eyes, rolling eyes, "
+    "weird eyes, smudged face, blurred face, poorly drawn face, mutation, mutilation, cloned face, strange mouth, "
+    "grainy, blurred, blurry, writing, calligraphy, signature, text, watermark, bad art,"
+)
+
 
 @dataclass
 class ModelConfig:

imaginairy/schema.py

@@ -94,6 +94,7 @@ class ImaginePrompt:
     def __init__(
         self,
         prompt=None,
+        negative_prompt=config.DEFAULT_NEGATIVE_PROMPT,
         prompt_strength=7.5,
         init_image=None,  # Pillow Image, LazyLoadingImage, or filepath str
         init_image_strength=0.3,
@@ -113,16 +114,11 @@ class ImaginePrompt:
         tile_mode=False,
         model=config.DEFAULT_MODEL,
     ):
-        prompt = prompt if prompt is not None else ""
-        fix_faces_fidelity = (
-            fix_faces_fidelity if fix_faces_fidelity else self.DEFAULT_FACE_FIDELITY
-        )
-        if isinstance(prompt, str):
-            self.prompts = [WeightedPrompt(prompt, 1)]
-        else:
-            self.prompts = prompt
-        self.prompts.sort(key=lambda p: p.weight, reverse=True)
+
+        self.prompts = self.process_prompt_input(prompt)
+        self.negative_prompt = self.process_prompt_input(negative_prompt)
         self.prompt_strength = prompt_strength
+
         if isinstance(init_image, str):
             init_image = LazyLoadingImage(filepath=init_image)
 
@@ -142,7 +138,9 @@ class ImaginePrompt:
         self.width = width
         self.upscale = upscale
         self.fix_faces = fix_faces
-        self.fix_faces_fidelity = fix_faces_fidelity
+        self.fix_faces_fidelity = (
+            fix_faces_fidelity if fix_faces_fidelity else self.DEFAULT_FACE_FIDELITY
+        )
         self.sampler_type = sampler_type.lower()
         self.conditioning = conditioning
         self.mask_prompt = mask_prompt
@@ -190,6 +188,15 @@ class ImaginePrompt:
             "sampler_type": self.sampler_type,
         }
 
+    def process_prompt_input(self, prompt_input):
+        prompt_input = prompt_input if prompt_input is not None else ""
+
+        if isinstance(prompt_input, str):
+            prompt_input = [WeightedPrompt(prompt_input, 1)]
+
+        prompt_input.sort(key=lambda p: p.weight, reverse=True)
+        return prompt_input
+
 
 class ExifCodes:
     """https://www.awaresystems.be/imaging/tiff/tifftags/baseline.html"""