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Merge branch 'beta' into bucketlite

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JeLuF 2023-08-01 17:17:37 +02:00
commit 2b49f6a8d0
9 changed files with 290 additions and 45 deletions
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1
CHANGES.md
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@ -22,6 +22,7 @@
Our focus continues to remain on an easy installation experience, and an easy user-interface. While still remaining pretty powerful, in terms of features and speed.
### Detailed changelog
* 2.5.48 - 1 Aug 2023 - (beta-only) Full support for ControlNets. You can select a control image to guide the AI. You can pick a filter to pre-process the image, and one of the known (or custom) controlnet models. Supports `OpenPose`, `Canny`, `Straight Lines`, `Depth`, `Line Art`, `Scribble`, `Soft Edge`, `Shuffle` and `Segment`.
* 2.5.47 - 30 Jul 2023 - An option to use `Strict Mask Border` while inpainting, to avoid touching areas outside the mask. But this might show a slight outline of the mask, which you will have to touch up separately.
* 2.5.47 - 29 Jul 2023 - (beta-only) Fix long prompts with SDXL.
* 2.5.47 - 29 Jul 2023 - (beta-only) Fix red dots in some SDXL images.

2
scripts/check_modules.py
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@ -18,7 +18,7 @@ os_name = platform.system()
modules_to_check = {
"torch": ("1.11.0", "1.13.1", "2.0.0"),
"torchvision": ("0.12.0", "0.14.1", "0.15.1"),
"sdkit": "1.0.153",
"sdkit": "1.0.156",
"stable-diffusion-sdkit": "2.1.4",
"rich": "12.6.0",
"uvicorn": "0.19.0",

54
ui/easydiffusion/model_manager.py
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@ -9,6 +9,7 @@ from easydiffusion.types import ModelsData
from easydiffusion.utils import log
from sdkit import Context
from sdkit.models import load_model, scan_model, unload_model, download_model, get_model_info_from_db
from sdkit.models.model_loader.controlnet_filters import filters as cn_filters
from sdkit.utils import hash_file_quick
KNOWN_MODEL_TYPES = [
@ -19,6 +20,8 @@ KNOWN_MODEL_TYPES = [
"realesrgan",
"lora",
"codeformer",
"embeddings",
"controlnet",
]
MODEL_EXTENSIONS = {
"stable-diffusion": [".ckpt", ".safetensors"],
@ -29,6 +32,7 @@ MODEL_EXTENSIONS = {
"lora": [".ckpt", ".safetensors"],
"codeformer": [".pth"],
"embeddings": [".pt", ".bin", ".safetensors"],
"controlnet": [".pth", ".safetensors"],
}
DEFAULT_MODELS = {
"stable-diffusion": [
@ -177,10 +181,17 @@ def reload_models_if_necessary(context: Context, models_data: ModelsData, models
def resolve_model_paths(models_data: ModelsData):
model_paths = models_data.model_paths
for model_type in model_paths:
if model_type in ("latent_upscaler", "nsfw_checker"): # doesn't use model paths
skip_models = cn_filters + ["latent_upscaler", "nsfw_checker"]
if model_type in skip_models: # doesn't use model paths
continue
if model_type == "codeformer":
download_if_necessary("codeformer", "codeformer.pth", "codeformer-0.1.0")
elif model_type == "controlnet":
model_id = model_paths[model_type]
model_info = get_model_info_from_db(model_type=model_type, model_id=model_id)
if model_info:
filename = model_info.get("url", "").split("/")[-1]
download_if_necessary("controlnet", filename, model_id, skip_if_others_exist=False)
model_paths[model_type] = resolve_model_to_use(model_paths[model_type], model_type=model_type)
@ -204,17 +215,17 @@ def download_default_models_if_necessary():
print(model_type, "model(s) found.")
def download_if_necessary(model_type: str, file_name: str, model_id: str):
def download_if_necessary(model_type: str, file_name: str, model_id: str, skip_if_others_exist=True):
model_path = os.path.join(app.MODELS_DIR, model_type, file_name)
expected_hash = get_model_info_from_db(model_type=model_type, model_id=model_id)["quick_hash"]
other_models_exist = any_model_exists(model_type)
other_models_exist = any_model_exists(model_type) and skip_if_others_exist
known_model_exists = os.path.exists(model_path)
known_model_is_corrupt = known_model_exists and hash_file_quick(model_path) != expected_hash
if known_model_is_corrupt or (not other_models_exist and not known_model_exists):
print("> download", model_type, model_id)
download_model(model_type, model_id, download_base_dir=app.MODELS_DIR)
download_model(model_type, model_id, download_base_dir=app.MODELS_DIR, download_config_if_available=False)
def migrate_legacy_model_location():
@ -285,12 +296,26 @@ def is_malicious_model(file_path):
def getModels(scan_for_malicious: bool = True):
models = {
"options": {
"stable-diffusion": ["sd-v1-4"],
"stable-diffusion": [{"sd-v1-4": "SD 1.4"}],
"vae": [],
"hypernetwork": [],
"lora": [],
"codeformer": ["codeformer"],
"codeformer": [{"codeformer": "CodeFormer"}],
"embeddings": [],
"controlnet": [
{"control_v11p_sd15_canny": "Canny (*)"},
{"control_v11p_sd15_openpose": "OpenPose (*)"},
{"control_v11p_sd15_normalbae": "Normal BAE (*)"},
{"control_v11f1p_sd15_depth": "Depth (*)"},
{"control_v11p_sd15_scribble": "Scribble"},
{"control_v11p_sd15_softedge": "Soft Edge"},
{"control_v11p_sd15_inpaint": "Inpaint"},
{"control_v11p_sd15_lineart": "Line Art"},
{"control_v11p_sd15s2_lineart_anime": "Line Art Anime"},
{"control_v11p_sd15_mlsd": "Straight Lines"},
{"control_v11p_sd15_seg": "Segment"},
{"control_v11e_sd15_shuffle": "Shuffle"},
],
},
}
@ -299,9 +324,9 @@ def getModels(scan_for_malicious: bool = True):
class MaliciousModelException(Exception):
"Raised when picklescan reports a problem with a model"
def scan_directory(directory, suffixes, directoriesFirst: bool = True):
def scan_directory(directory, suffixes, directoriesFirst: bool = True, default_entries=[]):
tree = list(default_entries)
nonlocal models_scanned
tree = []
for entry in sorted(
os.scandir(directory),
key=lambda entry: (entry.is_file() == directoriesFirst, entry.name.lower()),
@ -320,7 +345,14 @@ def getModels(scan_for_malicious: bool = True):
raise MaliciousModelException(entry.path)
if scan_for_malicious:
known_models[entry.path] = mtime
tree.append(entry.name[: -len(matching_suffix)])
model_id = entry.name[: -len(matching_suffix)]
model_exists = False
for m in tree: # allows default "named" models, like CodeFormer and known ControlNet models
if (isinstance(m, str) and model_id == m) or (isinstance(m, dict) and model_id in m):
model_exists = True
break
if not model_exists:
tree.append(model_id)
elif entry.is_dir():
scan = scan_directory(entry.path, suffixes, directoriesFirst=False)
@ -337,7 +369,8 @@ def getModels(scan_for_malicious: bool = True):
os.makedirs(models_dir)
try:
models["options"][model_type] = scan_directory(models_dir, model_extensions)
default_tree = models["options"].get(model_type, [])
models["options"][model_type] = scan_directory(models_dir, model_extensions, default_entries=default_tree)
except MaliciousModelException as e:
models["scan-error"] = str(e)
@ -350,6 +383,7 @@ def getModels(scan_for_malicious: bool = True):
listModels(model_type="gfpgan")
listModels(model_type="lora")
listModels(model_type="embeddings")
listModels(model_type="controlnet")
if scan_for_malicious and models_scanned > 0:
log.info(f"[green]Scanned {models_scanned} models. Nothing infected[/]")

27
ui/easydiffusion/tasks/render_images.py
View File

@ -63,7 +63,7 @@ class RenderTask(Task):
if (
runtime.set_vram_optimizations(context)
or self.has_param_changed(context, "clip_skip")
or self.has_param_changed(context, "convert_to_tensorrt")
or self.trt_needs_reload(context)
):
models_to_force_reload.append("stable-diffusion")
@ -92,6 +92,17 @@ class RenderTask(Task):
new_val = self.models_data.model_params.get("stable-diffusion", {}).get(param_name, False)
return model["params"].get(param_name) != new_val
def trt_needs_reload(self, context):
if not self.has_param_changed(context, "convert_to_tensorrt"):
return False
model = context.models["stable-diffusion"]
pipe = model["default"]
if hasattr(pipe.unet, "_allocate_trt_buffers"): # TRT already loaded
return False
return True
def make_images(
context,
@ -148,6 +159,7 @@ def make_images_internal(
context,
req,
task_data,
models_data,
data_queue,
task_temp_images,
step_callback,
@ -174,6 +186,7 @@ def generate_images_internal(
context,
req: GenerateImageRequest,
task_data: TaskData,
models_data: ModelsData,
data_queue: queue.Queue,
task_temp_images: list,
step_callback,
@ -197,6 +210,18 @@ def generate_images_internal(
if req.init_image is not None and not context.test_diffusers:
req.sampler_name = "ddim"
if req.control_image and task_data.control_filter_to_apply:
req.control_image = filter_images(context, req.control_image, task_data.control_filter_to_apply)[0]
if context.test_diffusers:
pipe = context.models["stable-diffusion"]["default"]
if hasattr(pipe.unet, "_allocate_trt_buffers"):
convert_to_trt = models_data.model_params["stable-diffusion"].get("convert_to_tensorrt", False)
pipe.unet.forward = pipe.unet._trt_forward if convert_to_trt else pipe.unet._non_trt_forward
# pipe.vae.decoder.forward = (
# pipe.vae.decoder._trt_forward if convert_to_trt else pipe.vae.decoder._non_trt_forward
# )
images = generate_images(context, callback=callback, **req.dict())
user_stopped = False
except UserInitiatedStop:

5
ui/easydiffusion/types.py
View File

@ -75,6 +75,7 @@ class TaskData(BaseModel):
use_controlnet_model: Union[str, List[str]] = None
filters: List[str] = []
filter_params: Dict[str, Dict[str, Any]] = {}
control_filter_to_apply: Union[str, List[str]] = None
show_only_filtered_image: bool = False
block_nsfw: bool = False
@ -135,6 +136,7 @@ class GenerateImageResponse:
def json(self):
del self.render_request.init_image
del self.render_request.init_image_mask
del self.render_request.control_image
task_data = self.task_data.dict()
task_data.update(self.output_format.dict())
@ -212,6 +214,9 @@ def convert_legacy_render_req_to_new(old_req: dict):
model_paths["latent_upscaler"] = (
model_paths["latent_upscaler"] if "latent_upscaler" in model_paths["latent_upscaler"].lower() else None
)
if "control_filter_to_apply" in old_req:
filter_model = old_req["control_filter_to_apply"]
model_paths[filter_model] = filter_model
if old_req.get("block_nsfw"):
model_paths["nsfw_checker"] = "nsfw_checker"

71
ui/index.html
View File

@ -34,7 +34,7 @@
<h1>
<img id="logo_img" src="/media/images/icon-512x512.png" >
Easy Diffusion
<small><span id="version">v2.5.47</span> <span id="updateBranchLabel"></span></small>
<small><span id="version">v2.5.48</span> <span id="updateBranchLabel"></span></small>
</h1>
</div>
<div id="server-status">
@ -85,8 +85,8 @@
<label for="init_image">Initial Image (img2img) <small>(optional)</small> </label>
<div id="init_image_preview_container" class="image_preview_container">
<div id="init_image_wrapper">
<img id="init_image_preview" src="" crossorigin="anonymous" />
<div id="init_image_wrapper" class="preview_image_wrapper">
<img id="init_image_preview" class="image_preview" src="" crossorigin="anonymous" />
<span id="init_image_size_box" class="img_bottom_label"></span>
<button class="init_image_clear image_clear_btn"><i class="fa-solid fa-xmark"></i></button>
</div>
@ -143,18 +143,17 @@
<div><table>
<tr><b class="settings-subheader">Image Settings</b></tr>
<tr class="pl-5"><td><label for="seed">Seed:</label></td><td><input id="seed" name="seed" size="10" value="0" onkeypress="preventNonNumericalInput(event)"> <input id="random_seed" name="random_seed" type="checkbox" checked><label for="random_seed">Random</label></td></tr>
<tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr>
<tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label id="num_outputs_parallel_label" for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr>
<tr class="pl-5"><td><label for="stable_diffusion_model">Model:</label></td><td class="model-input">
<input id="stable_diffusion_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<button id="reload-models" class="secondaryButton reloadModels"><i class='fa-solid fa-rotate'></i></button>
<a href="https://github.com/easydiffusion/easydiffusion/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about custom models</span></i></a>
</td></tr>
<tr class="pl-5 displayNone" id="enable_trt_config">
<td><label for="convert_to_tensorrt">Convert to TensorRT:</label></td>
<td><label for="convert_to_tensorrt">Enable TensorRT:</label></td>
<td class="diffusers-restart-needed">
<input id="convert_to_tensorrt" name="convert_to_tensorrt" type="checkbox">
<a href="https://github.com/easydiffusion/easydiffusion/wiki/TensorRT" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about TensorRT</span></i></a>
<label><small>Takes upto 20 mins the first time</small></label>
<!-- <label><small>Takes upto 20 mins the first time</small></label> -->
</td>
</tr>
<tr class="pl-5 displayNone" id="clip_skip_config">
@ -164,6 +163,60 @@
<a href="https://github.com/easydiffusion/easydiffusion/wiki/Clip-Skip" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about Clip Skip</span></i></a>
</td>
</tr>
<tr id="controlnet_model_container" class="pl-5"><td><label for="controlnet_model">ControlNet Image:</label></td><td>
<div id="control_image_wrapper" class="preview_image_wrapper">
<img id="control_image_preview" class="image_preview" src="" crossorigin="anonymous" />
<span id="control_image_size_box" class="img_bottom_label"></span>
<button class="control_image_clear image_clear_btn"><i class="fa-solid fa-xmark"></i></button>
</div>
<input id="control_image" name="control_image" type="file" />
<a href="https://github.com/easydiffusion/easydiffusion/wiki/ControlNet" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about ControlNets</span></i></a>
<div id="controlnet_config" class="displayNone">
<label><small>Filter to apply:</small></label>
<select id="control_image_filter">
<option value="">None</option>
<optgroup label="Pose">
<option value="openpose">OpenPose (*)</option>
<option value="openpose_face">OpenPose face</option>
<option value="openpose_faceonly">OpenPose face-only</option>
<option value="openpose_hand">OpenPose hand</option>
<option value="openpose_full">OpenPose full</option>
</optgroup>
<optgroup label="Outline">
<option value="canny">Canny (*)</option>
<option value="mlsd">Straight lines</option>
<option value="scribble_hed">Scribble hed (*)</option>
<option value="scribble_hedsafe">Scribble hedsafe</option>
<option value="scribble_pidinet">Scribble pidinet</option>
<option value="scribble_pidsafe">Scribble pidsafe</option>
<option value="softedge_hed">Softedge hed</option>
<option value="softedge_hedsafe">Softedge hedsafe</option>
<option value="softedge_pidinet">Softedge pidinet</option>
<option value="softedge_pidsafe">Softedge pidsafe</option>
</optgroup>
<optgroup label="Depth">
<option value="normal_bae">Normal bae (*)</option>
<option value="depth_midas">Depth midas</option>
<option value="depth_zoe">Depth zoe</option>
<option value="depth_leres">Depth leres</option>
<option value="depth_leres++">Depth leres++</option>
</optgroup>
<optgroup label="Line art">
<option value="lineart_coarse">Lineart coarse</option>
<option value="lineart_realistic">Lineart realistic</option>
<option value="lineart_anime">Lineart anime</option>
</optgroup>
<optgroup label="Misc">
<option value="shuffle">Shuffle</option>
<option value="segment">Segment</option>
</optgroup>
</select>
<br/>
<label for="controlnet_model"><small>Model:</small></label> <input id="controlnet_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<br/>
<label><small>Will download the necessary models, the first time.</small></label>
</div>
</td></tr>
<tr class="pl-5"><td><label for="vae_model">Custom VAE:</label></td><td>
<input id="vae_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" />
<a href="https://github.com/easydiffusion/easydiffusion/wiki/VAE-Variational-Auto-Encoder" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about VAEs</span></i></a>
@ -241,7 +294,7 @@
</select>
<label for="height"><small>(height)</small></label>
<div id="recent-resolutions-container">
<span id="recent-resolutions-button" class="clickable"><i class="fa-solid fa-sliders"><span class="simple-tooltip top-left"> Recent sizes </span></i></span>
<span id="recent-resolutions-button" class="clickable"><i class="fa-solid fa-sliders"><span class="simple-tooltip top-left"> Advanced sizes </span></i></span>
<div id="recent-resolutions-popup" class="displayNone">
<small>Custom size:</small><br>
<input id="custom-width" name="custom-width" type="number" min="128" value="512" onkeypress="preventNonNumericalInput(event)">
@ -737,7 +790,7 @@ async function init() {
ping: onPing
}
})
splashScreen()
// splashScreen()
// load models again, but scan for malicious this time
await getModels(true)

16
ui/media/css/main.css
View File

@ -794,7 +794,7 @@ div.img-preview img {
margin-bottom: 8px;
}
#init_image_preview_container:not(.has-image) #init_image_wrapper,
#init_image_preview_container:not(.has-image) .preview_image_wrapper,
#init_image_preview_container:not(.has-image) #inpaint_button_container {
display: none;
}
@ -831,14 +831,14 @@ div.img-preview img {
gap: 8px;
}
#init_image_wrapper {
.preview_image_wrapper {
grid-row: span 3;
position: relative;
width: fit-content;
max-height: 150px;
}
#init_image_preview {
.image_preview {
max-height: 150px;
height: 100%;
width: 100%;
@ -1843,3 +1843,13 @@ div#enlarge-buttons {
.imgContainer .spinnerStatus {
font-size: 10pt;
}
#controlnet_model_container small {
color: var(--text-color)
}
#control_image {
width: 130pt;
}
#controlnet_model {
width: 77%;
}

126
ui/media/js/main.js
View File

@ -93,6 +93,11 @@ let initImagePreview = document.querySelector("#init_image_preview")
let initImageSizeBox = document.querySelector("#init_image_size_box")
let maskImageSelector = document.querySelector("#mask")
let maskImagePreview = document.querySelector("#mask_preview")
let controlImageSelector = document.querySelector("#control_image")
let controlImagePreview = document.querySelector("#control_image_preview")
let controlImageClearBtn = document.querySelector(".control_image_clear")
let controlImageContainer = document.querySelector("#control_image_wrapper")
let controlImageFilterField = document.querySelector("#control_image_filter")
let applyColorCorrectionField = document.querySelector("#apply_color_correction")
let strictMaskBorderField = document.querySelector("#strict_mask_border")
let colorCorrectionSetting = document.querySelector("#apply_color_correction_setting")
@ -114,6 +119,7 @@ let codeformerFidelityField = document.querySelector("#codeformer_fidelity")
let stableDiffusionModelField = new ModelDropdown(document.querySelector("#stable_diffusion_model"), "stable-diffusion")
let clipSkipField = document.querySelector("#clip_skip")
let tilingField = document.querySelector("#tiling")
let controlnetModelField = new ModelDropdown(document.querySelector("#controlnet_model"), "controlnet", "None", false)
let vaeModelField = new ModelDropdown(document.querySelector("#vae_model"), "vae", "None")
let hypernetworkModelField = new ModelDropdown(document.querySelector("#hypernetwork_model"), "hypernetwork", "None")
let hypernetworkStrengthSlider = document.querySelector("#hypernetwork_strength_slider")
@ -1378,9 +1384,19 @@ function createTask(task) {
function getCurrentUserRequest() {
const numOutputsTotal = parseInt(numOutputsTotalField.value)
const numOutputsParallel = parseInt(numOutputsParallelField.value)
let numOutputsParallel = parseInt(numOutputsParallelField.value)
const seed = randomSeedField.checked ? Math.floor(Math.random() * (2 ** 32 - 1)) : parseInt(seedField.value)
if (
testDiffusers.checked &&
document.getElementById("toggle-tensorrt-install").innerHTML == "Uninstall" &&
document.querySelector("#convert_to_tensorrt").checked
) {
// TRT enabled
numOutputsParallel = 1 // force 1 parallel
}
const newTask = {
batchesDone: 0,
numOutputsTotal: numOutputsTotal,
@ -1469,6 +1485,13 @@ function getCurrentUserRequest() {
// TRT is installed
newTask.reqBody.convert_to_tensorrt = document.querySelector("#convert_to_tensorrt").checked
}
if (controlnetModelField.value !== "" && IMAGE_REGEX.test(controlImagePreview.src)) {
newTask.reqBody.use_controlnet_model = controlnetModelField.value
newTask.reqBody.control_image = controlImagePreview.src
if (controlImageFilterField.value !== "") {
newTask.reqBody.control_filter_to_apply = controlImageFilterField.value
}
}
return newTask
}
@ -1875,6 +1898,51 @@ function onFixFaceModelChange() {
gfpganModelField.addEventListener("change", onFixFaceModelChange)
onFixFaceModelChange()
function onControlnetModelChange() {
let configBox = document.querySelector("#controlnet_config")
if (IMAGE_REGEX.test(controlImagePreview.src)) {
configBox.classList.remove("displayNone")
controlImageContainer.classList.remove("displayNone")
} else {
configBox.classList.add("displayNone")
controlImageContainer.classList.add("displayNone")
}
}
controlImagePreview.addEventListener("load", onControlnetModelChange)
controlImagePreview.addEventListener("unload", onControlnetModelChange)
onControlnetModelChange()
function onControlImageFilterChange() {
let filterId = controlImageFilterField.value
if (filterId.includes("openpose")) {
controlnetModelField.value = "control_v11p_sd15_openpose"
} else if (filterId === "canny") {
controlnetModelField.value = "control_v11p_sd15_canny"
} else if (filterId === "mlsd") {
controlnetModelField.value = "control_v11p_sd15_mlsd"
} else if (filterId === "mlsd") {
controlnetModelField.value = "control_v11p_sd15_mlsd"
} else if (filterId.includes("scribble")) {
controlnetModelField.value = "control_v11p_sd15_scribble"
} else if (filterId.includes("softedge")) {
controlnetModelField.value = "control_v11p_sd15_softedge"
} else if (filterId === "normal_bae") {
controlnetModelField.value = "control_v11p_sd15_normalbae"
} else if (filterId.includes("depth")) {
controlnetModelField.value = "control_v11f1p_sd15_depth"
} else if (filterId === "lineart_anime") {
controlnetModelField.value = "control_v11p_sd15s2_lineart_anime"
} else if (filterId.includes("lineart")) {
controlnetModelField.value = "control_v11p_sd15_lineart"
} else if (filterId === "shuffle") {
controlnetModelField.value = "control_v11e_sd15_shuffle"
} else if (filterId === "segment") {
controlnetModelField.value = "control_v11p_sd15_seg"
}
}
controlImageFilterField.addEventListener("change", onControlImageFilterChange)
onControlImageFilterChange()
upscaleModelField.disabled = !useUpscalingField.checked
upscaleAmountField.disabled = !useUpscalingField.checked
useUpscalingField.addEventListener("change", function(e) {
@ -2165,6 +2233,44 @@ promptsFromFileBtn.addEventListener("click", function() {
promptsFromFileSelector.click()
})
function loadControlnetImageFromFile() {
if (controlImageSelector.files.length === 0) {
return
}
let reader = new FileReader()
let file = controlImageSelector.files[0]
reader.addEventListener("load", function(event) {
controlImagePreview.src = reader.result
})
if (file) {
reader.readAsDataURL(file)
}
}
controlImageSelector.addEventListener("change", loadControlnetImageFromFile)
function controlImageLoad() {
let w = controlImagePreview.naturalWidth
let h = controlImagePreview.naturalHeight
addImageSizeOption(w)
addImageSizeOption(h)
widthField.value = w
heightField.value = h
widthField.dispatchEvent(new Event("change"))
heightField.dispatchEvent(new Event("change"))
}
controlImagePreview.addEventListener("load", controlImageLoad)
function controlImageUnload() {
controlImageSelector.value = null
controlImagePreview.src = ""
controlImagePreview.dispatchEvent(new Event("unload"))
}
controlImageClearBtn.addEventListener("click", controlImageUnload)
promptsFromFileSelector.addEventListener("change", async function() {
if (promptsFromFileSelector.files.length === 0) {
return
@ -2293,6 +2399,8 @@ function tunnelUpdate(event) {
}
}
let trtSettingsForced = false
function packagesUpdate(event) {
let trtBtn = document.getElementById("toggle-tensorrt-install")
let trtInstalled = "packages_installed" in event && "tensorrt" in event["packages_installed"]
@ -2307,6 +2415,22 @@ function packagesUpdate(event) {
if (document.getElementById("toggle-tensorrt-install").innerHTML == "Uninstall") {
document.querySelector("#enable_trt_config").classList.remove("displayNone")
if (!trtSettingsForced) {
// settings for demo
promptField.value = "Dragons fighting with a knight, castle, war scene, fantasy, cartoon, flames, HD"
seedField.value = 3187947173
widthField.value = 1024
heightField.value = 768
randomSeedField.checked = false
seedField.disabled = false
stableDiffusionModelField.value = "sd-v1-4"
numOutputsParallelField.classList.add("displayNone")
document.querySelector("#num_outputs_parallel_label").classList.add("displayNone")
trtSettingsForced = true
}
}
}

33
ui/media/js/searchable-models.js
View File

@ -552,17 +552,23 @@ class ModelDropdown {
this.createModelNodeList(`${folderName || ""}/${childFolderName}`, childModels, false)
)
} else {
let modelId = model
let modelName = model
if (typeof model === "object") {
modelId = Object.keys(model)[0]
modelName = model[modelId]
}
const classes = ["model-file"]
if (isRootFolder) {
classes.push("in-root-folder")
}
// Remove the leading slash from the model path
const fullPath = folderName ? `${folderName.substring(1)}/${model}` : model
const fullPath = folderName ? `${folderName.substring(1)}/${modelId}` : modelId
modelsMap.set(
model,
modelId,
createElement("li", { "data-path": fullPath }, classes, [
createElement("i", undefined, ["fa-regular", "fa-file", "icon"]),
model,
modelName,
])
)
}
@ -643,22 +649,6 @@ async function getModels(scanForMalicious = true) {
makeImageBtn.disabled = true
}
/* This code should no longer be needed. Commenting out for now, will cleanup later.
const sd_model_setting_key = "stable_diffusion_model"
const vae_model_setting_key = "vae_model"
const hypernetwork_model_key = "hypernetwork_model"
const stableDiffusionOptions = modelsOptions['stable-diffusion']
const vaeOptions = modelsOptions['vae']
const hypernetworkOptions = modelsOptions['hypernetwork']
// TODO: set default for model here too
SETTINGS[sd_model_setting_key].default = stableDiffusionOptions[0]
if (getSetting(sd_model_setting_key) == '' || SETTINGS[sd_model_setting_key].value == '') {
setSetting(sd_model_setting_key, stableDiffusionOptions[0])
}
*/
// notify ModelDropdown objects to refresh
document.dispatchEvent(new Event("refreshModels"))
} catch (e) {
@ -667,4 +657,7 @@ async function getModels(scanForMalicious = true) {
}
// reload models button
document.querySelector("#reload-models").addEventListener("click", () => getModels())
document.querySelector("#reload-models").addEventListener("click", (e) => {
e.stopPropagation()
getModels()
})