Auto-update: Sun Jun 30 08:36:43 PDT 2024

This commit is contained in:
sanj 2024-06-30 08:36:43 -07:00
parent dadd5421ea
commit ebf34c645b
6 changed files with 1005 additions and 489 deletions

View file

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View file

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"4", "4",
@ -81,25 +87,25 @@
}, },
"13": { "13": {
"inputs": { "inputs": {
"seed": 1125631171146107, "seed": 686880884118590,
"steps": 10, "steps": 10,
"cfg": 1.8, "cfg": 1.8,
"sampler_name": "dpmpp_2s_ancestral", "sampler_name": "dpmpp_sde",
"scheduler": "karras", "scheduler": "karras",
"start_at_step": 0, "start_at_step": 0,
"end_at_step": 10000, "end_at_step": 10000,
"enable_denoise": "false", "enable_denoise": "false",
"denoise": 1, "denoise": 1,
"add_noise": "enable", "add_noise": "enable",
"return_with_leftover_noise": "enable", "return_with_leftover_noise": "disable",
"noise_type": "brownian_fractal", "noise_type": "brownian_fractal",
"noise_blending": "cuberp", "noise_blending": "cuberp",
"noise_mode": "additive", "noise_mode": "additive",
"scale": 1, "scale": 1,
"alpha_exponent": 1, "alpha_exponent": 1,
"modulator": 1, "modulator": 1.05,
"sigma_tolerance": 0.5, "sigma_tolerance": 0.5,
"boost_leading_sigma": "false", "boost_leading_sigma": "true",
"guide_use_noise": "true", "guide_use_noise": "true",
"model": [ "model": [
"4", "4",
@ -138,13 +144,13 @@
"Z": 0, "Z": 0,
"evolution": 0, "evolution": 0,
"frame": 0, "frame": 0,
"scale": 5, "scale": 2.5,
"octaves": 5, "octaves": 5,
"persistence": 4, "persistence": 4,
"lacunarity": 5, "lacunarity": 3,
"exponent": 4.28, "exponent": 2,
"brightness": -0.3, "brightness": -0.1,
"contrast": -0.2 "contrast": -0.1
}, },
"class_type": "Perlin Power Fractal Settings (PPF Noise)", "class_type": "Perlin Power Fractal Settings (PPF Noise)",
"_meta": { "_meta": {
@ -155,12 +161,12 @@
"inputs": { "inputs": {
"frequency": 332.65500000000003, "frequency": 332.65500000000003,
"octaves": 32, "octaves": 32,
"persistence": 1.616, "persistence": 1.4000000000000001,
"num_colors": 256, "num_colors": 128,
"color_tolerance": 0.05, "color_tolerance": 0.05,
"angle_degrees": 180, "angle_degrees": 45,
"brightness": -0.5, "brightness": -0.25,
"contrast": -0.05, "contrast": 0,
"blur": 1.3 "blur": 1.3
}, },
"class_type": "Cross-Hatch Power Fractal Settings (PPF Noise)", "class_type": "Cross-Hatch Power Fractal Settings (PPF Noise)",
@ -209,19 +215,10 @@
"title": "ConditioningZeroOut" "title": "ConditioningZeroOut"
} }
}, },
"24": {
"inputs": {
"model_name": "RealESRGAN_x4plus.pth"
},
"class_type": "UpscaleModelLoader",
"_meta": {
"title": "Load Upscale Model"
}
},
"26": { "26": {
"inputs": { "inputs": {
"upscale_model": [ "upscale_model": [
"24", "58",
0 0
], ],
"image": [ "image": [
@ -236,7 +233,7 @@
}, },
"27": { "27": {
"inputs": { "inputs": {
"factor": 0.5, "factor": 0.25,
"interpolation_mode": "bicubic", "interpolation_mode": "bicubic",
"image": [ "image": [
"30", "30",
@ -280,62 +277,310 @@
}, },
"39": { "39": {
"inputs": { "inputs": {
"upscale_by": 2, "noise_seed": 690275685743412,
"seed": 687912408861107, "steps": 16,
"steps": 20, "cfg": 7.5,
"cfg": 1.9000000000000001, "base_ratio": 0.85,
"sampler_name": "heun", "denoise": 0.25,
"scheduler": "sgm_uniform", "scaled_width": [
"denoise": 0.2, "60",
"mode_type": "Linear", 0
"tile_width": 512, ],
"tile_height": 512, "scaled_height": [
"mask_blur": 8, "64",
"tile_padding": 32, 0
"seam_fix_mode": "Band Pass", ],
"seam_fix_denoise": 1, "noise_offset": 1,
"seam_fix_width": 64, "refiner_strength": 1,
"seam_fix_mask_blur": 8, "softness": 0,
"seam_fix_padding": 16, "base_model": [
"force_uniform_tiles": true, "40",
"tiled_decode": true, 0
],
"base_positive": [
"45",
0
],
"base_negative": [
"46",
0
],
"refiner_model": [
"42",
0
],
"refiner_positive": [
"43",
0
],
"refiner_negative": [
"44",
0
],
"image": [ "image": [
"38", "38",
0 0
], ],
"model": [
"4",
0
],
"positive": [
"6",
0
],
"negative": [
"23",
0
],
"vae": [ "vae": [
"4", "41",
2 2
], ],
"sampler_name": [
"47",
0
],
"scheduler": [
"47",
1
],
"upscale_model": [ "upscale_model": [
"40", "58",
0 0
] ]
}, },
"class_type": "UltimateSDUpscale", "class_type": "SeargeSDXLImage2ImageSampler2",
"_meta": { "_meta": {
"title": "Ultimate SD Upscale" "title": "Image2Image Sampler v2 (Searge)"
} }
}, },
"40": { "40": {
"inputs": { "inputs": {
"model_name": "RealESRGAN_x2.pth" "lora_name": "SDXL/SDXLLandskaper_v1-000003.safetensors",
"strength_model": 1,
"strength_clip": 1,
"model": [
"48",
0
],
"clip": [
"48",
1
]
},
"class_type": "LoraLoader",
"_meta": {
"title": "Load LoRA"
}
},
"41": {
"inputs": {
"ckpt_name": "SDXL/realismEngineSDXL_v20VAE.safetensors"
},
"class_type": "CheckpointLoaderSimple",
"_meta": {
"title": "Load Checkpoint"
}
},
"42": {
"inputs": {
"ckpt_name": "SDXL/sdxl_refiner_1.0.safetensors"
},
"class_type": "CheckpointLoaderSimple",
"_meta": {
"title": "Load Checkpoint"
}
},
"43": {
"inputs": {
"text": [
"50",
0
],
"clip": [
"42",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"44": {
"inputs": {
"text": [
"51",
0
],
"clip": [
"42",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"45": {
"inputs": {
"text": [
"50",
0
],
"clip": [
"40",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"46": {
"inputs": {
"text": [
"51",
0
],
"clip": [
"40",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"47": {
"inputs": {
"sampler_name": "dpmpp_2m_sde",
"scheduler": "karras"
},
"class_type": "SeargeSamplerInputs",
"_meta": {
"title": "Sampler Settings"
}
},
"48": {
"inputs": {
"lora_name": "SDXL/add-detail-xl.safetensors",
"strength_model": 1,
"strength_clip": 1,
"model": [
"41",
0
],
"clip": [
"41",
1
]
},
"class_type": "LoraLoader",
"_meta": {
"title": "Load LoRA"
}
},
"50": {
"inputs": {
"text": "API_PrePrompt"
},
"class_type": "JWStringMultiline",
"_meta": {
"title": "String (Multiline)"
}
},
"51": {
"inputs": {
"text": "API_NegativePrompt"
},
"class_type": "JWStringMultiline",
"_meta": {
"title": "String (Multiline)"
}
},
"52": {
"inputs": {
"image": [
"38",
0
]
},
"class_type": "Image Size to Number",
"_meta": {
"title": "Image Size to Number"
}
},
"55": {
"inputs": {
"op": "a * b",
"a": [
"52",
2
],
"b": [
"65",
0
],
"c": 0
},
"class_type": "SeargeFloatMath",
"_meta": {
"title": "Float Math"
}
},
"58": {
"inputs": {
"model_name": "4x_foolhardy_Remacri.pth"
}, },
"class_type": "UpscaleModelLoader", "class_type": "UpscaleModelLoader",
"_meta": { "_meta": {
"title": "Load Upscale Model" "title": "Load Upscale Model"
} }
},
"59": {
"inputs": {
"op": "a * b",
"a": [
"52",
3
],
"b": [
"65",
0
],
"c": 0
},
"class_type": "SeargeFloatMath",
"_meta": {
"title": "Float Math"
}
},
"60": {
"inputs": {
"value": [
"55",
0
],
"mode": "round"
},
"class_type": "JWFloatToInteger",
"_meta": {
"title": "Float to Integer"
}
},
"64": {
"inputs": {
"value": [
"59",
0
],
"mode": "round"
},
"class_type": "JWFloatToInteger",
"_meta": {
"title": "Float to Integer"
}
},
"65": {
"inputs": {
"value": 2
},
"class_type": "JWFloat",
"_meta": {
"title": "Float"
}
} }
} }

View file

@ -1,281 +0,0 @@
{
"4": {
"inputs": {
"ckpt_name": "Other/dreamshaperXL_v21TurboDPMSDE.safetensors"
},
"class_type": "CheckpointLoaderSimple",
"_meta": {
"title": "Load Checkpoint"
}
},
"6": {
"inputs": {
"text": "API_PrePrompt",
"clip": [
"4",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"7": {
"inputs": {
"text": "API_NegativePrompt",
"clip": [
"4",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"8": {
"inputs": {
"samples": [
"13",
0
],
"vae": [
"4",
2
]
},
"class_type": "VAEDecode",
"_meta": {
"title": "VAE Decode"
}
},
"9": {
"inputs": {
"filename_prefix": "API_",
"images": [
"27",
0
]
},
"class_type": "SaveImage",
"_meta": {
"title": "Save Image"
}
},
"11": {
"inputs": {
"batch_size": 1,
"width": 1023,
"height": 1024,
"resampling": "nearest-exact",
"X": 0,
"Y": 0,
"Z": 0,
"evolution": 0,
"frame": 0,
"scale": 5,
"octaves": 8,
"persistence": 1.5,
"lacunarity": 2,
"exponent": 4,
"brightness": 0,
"contrast": 0,
"clamp_min": 0,
"clamp_max": 1,
"seed": 490162938389882,
"device": "cpu",
"optional_vae": [
"4",
2
]
},
"class_type": "Perlin Power Fractal Latent (PPF Noise)",
"_meta": {
"title": "Perlin Power Fractal Noise 🦚"
}
},
"13": {
"inputs": {
"seed": 697312143874418,
"steps": 8,
"cfg": 1.6,
"sampler_name": "dpmpp_2m_sde",
"scheduler": "karras",
"start_at_step": 0,
"end_at_step": 10000,
"enable_denoise": "false",
"denoise": 1,
"add_noise": "enable",
"return_with_leftover_noise": "disable",
"noise_type": "brownian_fractal",
"noise_blending": "cuberp",
"noise_mode": "additive",
"scale": 1,
"alpha_exponent": 1,
"modulator": 1,
"sigma_tolerance": 0.5,
"boost_leading_sigma": "false",
"guide_use_noise": "true",
"model": [
"4",
0
],
"positive": [
"20",
0
],
"negative": [
"7",
0
],
"latent_image": [
"11",
0
],
"ppf_settings": [
"14",
0
],
"ch_settings": [
"15",
0
]
},
"class_type": "Power KSampler Advanced (PPF Noise)",
"_meta": {
"title": "Power KSampler Advanced 🦚"
}
},
"14": {
"inputs": {
"X": 0,
"Y": 0,
"Z": 0,
"evolution": 0,
"frame": 0,
"scale": 5,
"octaves": 8,
"persistence": 1.5,
"lacunarity": 2,
"exponent": 4,
"brightness": 0,
"contrast": 0
},
"class_type": "Perlin Power Fractal Settings (PPF Noise)",
"_meta": {
"title": "Perlin Power Fractal Settings 🦚"
}
},
"15": {
"inputs": {
"frequency": 320,
"octaves": 12,
"persistence": 1.5,
"num_colors": 16,
"color_tolerance": 0.05,
"angle_degrees": 45,
"brightness": 0,
"contrast": 0,
"blur": 2.5
},
"class_type": "Cross-Hatch Power Fractal Settings (PPF Noise)",
"_meta": {
"title": "Cross-Hatch Power Fractal Settings 🦚"
}
},
"20": {
"inputs": {
"conditioning_1": [
"6",
0
],
"conditioning_2": [
"21",
0
]
},
"class_type": "ConditioningCombine",
"_meta": {
"title": "Conditioning (Combine)"
}
},
"21": {
"inputs": {
"text": "API_StylePrompt",
"clip": [
"4",
1
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"23": {
"inputs": {
"conditioning": [
"7",
0
]
},
"class_type": "ConditioningZeroOut",
"_meta": {
"title": "ConditioningZeroOut"
}
},
"24": {
"inputs": {
"model_name": "ESRGAN_SRx4_DF2KOST_official-ff704c30.pth"
},
"class_type": "UpscaleModelLoader",
"_meta": {
"title": "Load Upscale Model"
}
},
"26": {
"inputs": {
"upscale_model": [
"24",
0
],
"image": [
"8",
0
]
},
"class_type": "ImageUpscaleWithModel",
"_meta": {
"title": "Upscale Image (using Model)"
}
},
"27": {
"inputs": {
"factor": 0.5,
"interpolation_mode": "bicubic",
"image": [
"30",
0
]
},
"class_type": "JWImageResizeByFactor",
"_meta": {
"title": "Image Resize by Factor"
}
},
"30": {
"inputs": {
"blur_radius": 3,
"sigma": 1.5,
"image": [
"26",
0
]
},
"class_type": "ImageBlur",
"_meta": {
"title": "ImageBlur"
}
}
}

View file

@ -333,6 +333,8 @@ async def generate_context(date_time, location: Location, forecast: str, mood: s
prompt = "Generate an aesthetically appealing banner image for a daily note that helps to visualize the following scene information: " prompt = "Generate an aesthetically appealing banner image for a daily note that helps to visualize the following scene information: "
prompt += "\n".join([display_name, forecast, mood, other_context]) prompt += "\n".join([display_name, forecast, mood, other_context])
return prompt
async def get_note(date_time: dt_datetime): async def get_note(date_time: dt_datetime):

View file

@ -235,6 +235,7 @@ def get_scene(scene):
SD_CONFIG = yaml.safe_load(SD_CONFIG_file) SD_CONFIG = yaml.safe_load(SD_CONFIG_file)
for scene_data in SD_CONFIG['scenes']: for scene_data in SD_CONFIG['scenes']:
if scene_data['scene'] == scene: if scene_data['scene'] == scene:
L.DEBUG(f"Found scene for \"{scene}\".")
return scene_data return scene_data
return None return None
@ -251,8 +252,13 @@ def get_matching_scene(prompt):
count = sum(1 for trigger in sc['triggers'] if trigger in prompt_lower) count = sum(1 for trigger in sc['triggers'] if trigger in prompt_lower)
if count > max_count: if count > max_count:
max_count = count max_count = count
L.DEBUG(f"Found better-matching scene: the prompt contains {max_count} words that match triggers for {scene_data.get('name')}!")
scene_data = sc scene_data = sc
return scene_data if scene_data else SD_CONFIG['scenes'][0] # fall back on first scene, which should be an appropriate default scene. if scene_data:
return scene_data
else:
L.DEBUG(f"No matching scenes found, falling back to default scene.")
return SD_CONFIG['scenes'][0]