Merge branch 'easydiffusion:beta' into beta

Update Branch

CHANGES.md

@@ -17,6 +17,8 @@
 - **Major rewrite of the code** - We've switched to using diffusers under-the-hood, which allows us to release new features faster, and focus on making the UI and installer even easier to use.
 
 ### Detailed changelog
+* 3.0.9 - 28 May 2024 - Slider for controlling the strength of controlnets.
+* 3.0.8 - 27 May 2024 - SDXL ControlNets for Img2Img and Inpainting.
 * 3.0.7 - 11 Dec 2023 - Setting to enable/disable VAE tiling (in the Image Settings panel). Sometimes VAE tiling reduces the quality of the image, so this setting will help control that.
 * 3.0.6 - 18 Sep 2023 - Add thumbnails to embeddings from the UI, using the new `Upload Thumbnail` button in the Embeddings popup. Thanks @JeLuf.
 * 3.0.6 - 15 Sep 2023 - Fix broken embeddings dialog when LoRA information couldn't be fetched.

scripts/check_modules.py

@@ -15,13 +15,16 @@ import traceback
 import shutil
 from pathlib import Path
 from pprint import pprint
+import re
 
 os_name = platform.system()
 
 modules_to_check = {
     "torch": ("1.11.0", "1.13.1", "2.0.0", "2.0.1"),
     "torchvision": ("0.12.0", "0.14.1", "0.15.1", "0.15.2"),
-    "sdkit": "2.0.15",
+    "setuptools": "69.5.1",
+    # "sdkit": "2.0.15.6", # checked later
+    # "diffusers": "0.21.4", # checked later
     "stable-diffusion-sdkit": "2.1.5",
     "rich": "12.6.0",
     "uvicorn": "0.19.0",
@@ -32,7 +35,7 @@ modules_to_check = {
     "python-multipart": "0.0.6",
     # "xformers": "0.0.16",
 }
-modules_to_log = ["torch", "torchvision", "sdkit", "stable-diffusion-sdkit"]
+modules_to_log = ["torch", "torchvision", "sdkit", "stable-diffusion-sdkit", "diffusers"]
 
 
 def version(module_name: str) -> str:
@@ -91,6 +94,14 @@ def update_modules():
 
         allowed_versions, latest_version = get_allowed_versions(module_name, allowed_versions)
 
+        if module_name == "setuptools":
+            if os_name == "Windows":
+                allowed_versions = ("59.8.0",)
+                latest_version = "59.8.0"
+            else:
+                allowed_versions = ("69.0.0",)
+                latest_version = "69.0.0"
+
         requires_install = False
         if module_name in ("torch", "torchvision"):
             if version(module_name) is None:  # allow any torch version
@@ -114,10 +125,112 @@ def update_modules():
                         f"WARNING! Tried to install {module_name}=={latest_version}, but the version is still {version(module_name)}!"
                     )
 
-        if module_name in modules_to_log:
+    # different sdkit versions, with the corresponding diffusers
+    #  if sdkit is 2.0.15.x (or lower), then diffusers should be restricted to 0.21.4 (see below for the reason)
+    #  otherwise use the current sdkit version (with the corresponding diffusers version)
+
+    expected_sdkit_version_str = "2.0.20.4"
+    expected_diffusers_version_str = "0.28.2"
+
+    legacy_sdkit_version_str = "2.0.15.7"
+    legacy_diffusers_version_str = "0.21.4"
+
+    sdkit_version_str = version("sdkit")
+    if sdkit_version_str is None:  # first install
+        _install("sdkit", expected_sdkit_version_str)
+        _install("diffusers", expected_diffusers_version_str)
+    else:
+        sdkit_version = version_str_to_tuple(sdkit_version_str)
+        legacy_sdkit_version = version_str_to_tuple(legacy_sdkit_version_str)
+
+        if sdkit_version[:3] <= legacy_sdkit_version[:3]:  # and torch_version < (0, 13):
+            # stick to diffusers 0.21.4, since it preserves torch 0.11+ compatibility.
+            # upgrading beyond this will result in a 2+ GB download of torch on older installations
+            #  and a time-consuming chain of small package updates due to huggingface_hub upgrade.
+            # for now, the user will need to explicitly upgrade to a newer sdkit, to break this ceiling.
+
+            install_pkg_if_necessary("sdkit", legacy_sdkit_version_str)
+            install_pkg_if_necessary("diffusers", legacy_diffusers_version_str)
+        else:
+            torch_version = version_str_to_tuple(version("torch"))
+            if torch_version < (1, 13):
+                # install the gpu-compatible torch (if necessary), instead of the default CPU-only one
+                # from the diffusers dependency chain
+                install("torch", modules_to_check["torch"][-1])
+                install("torchvision", modules_to_check["torchvision"][-1])
+
+            install_pkg_if_necessary("sdkit", expected_sdkit_version_str)
+            install_pkg_if_necessary("diffusers", expected_diffusers_version_str)
+
+    # hotfix accelerate
+    accelerate_version = version("accelerate")
+    if accelerate_version is None:
+        install("accelerate", "0.23.0")
+    else:
+        accelerate_version = accelerate_version.split(".")
+        accelerate_version = tuple(map(int, accelerate_version))
+        if accelerate_version < (0, 23):
+            install("accelerate", "0.23.0")
+
+    # hotfix - 29 May 2024. sdkit has stopped pulling its dependencies for some reason
+    # temporarily dumping sdkit's requirements here:
+    if os_name != "Windows":
+        sdkit_deps = [
+            "gfpgan",
+            "piexif",
+            "realesrgan",
+            "requests",
+            "picklescan",
+            "safetensors==0.3.3",
+            "k-diffusion==0.0.12",
+            "compel==2.0.1",
+            "controlnet-aux==0.0.6",
+            "invisible-watermark==0.2.0",  # required for SD XL
+        ]
+
+        for mod in sdkit_deps:
+            mod_name = mod
+            mod_force_version_str = None
+            if "==" in mod:
+                mod_name, mod_force_version_str = mod.split("==")
+
+            curr_mod_version_str = version(mod_name)
+            if curr_mod_version_str is None:
+                _install(mod_name, mod_force_version_str)
+            elif mod_force_version_str is not None:
+                curr_mod_version = version_str_to_tuple(curr_mod_version_str)
+                mod_force_version = version_str_to_tuple(mod_force_version_str)
+
+                if curr_mod_version != mod_force_version:
+                    _install(mod_name, mod_force_version_str)
+
+    for module_name in modules_to_log:
         print(f"{module_name}: {version(module_name)}")
 
 
+def _install(module_name, module_version=None):
+    if module_version is None:
+        install_cmd = f"python -m pip install {module_name}"
+    else:
+        install_cmd = f"python -m pip install --upgrade {module_name}=={module_version}"
+
+    print(">", install_cmd)
+    os.system(install_cmd)
+
+
+def install_pkg_if_necessary(pkg_name, required_version):
+    pkg_version = version(pkg_name)
+    if pkg_version != required_version:
+        _install(pkg_name, required_version)
+
+
+def version_str_to_tuple(ver_str):
+    ver_str = ver_str.split("+")[0]
+    ver_str = re.sub("[^0-9.]", "", ver_str)
+    ver = ver_str.split(".")
+    return tuple(map(int, ver))
+
+
 ### utilities
 
 
@@ -302,8 +415,16 @@ def launch_uvicorn():
         setup_amd_environment()
 
     print("\nLaunching uvicorn\n")
-    os.system(
+
-        f'python -m uvicorn main:server_api --app-dir "{os.environ["SD_UI_PATH"]}" --port {listen_port} --host {bind_ip} --log-level error'
+    import uvicorn
+
+    uvicorn.run(
+        "main:server_api",
+        port=listen_port,
+        log_level="error",
+        app_dir=os.environ["SD_UI_PATH"],
+        host=bind_ip,
+        access_log=False,
     )
 
 

ui/easydiffusion/device_manager.py

@@ -243,6 +243,7 @@ def get_processor_name():
         if platform.system() == "Windows":
             return platform.processor()
         elif platform.system() == "Darwin":
+            if "/usr/sbin" not in os.environ["PATH"].split(os.pathsep):
                 os.environ["PATH"] = os.environ["PATH"] + os.pathsep + "/usr/sbin"
             command = "sysctl -n machdep.cpu.brand_string"
             return subprocess.check_output(command, shell=True).decode().strip()

ui/easydiffusion/utils/save_utils.py

@@ -31,6 +31,7 @@ TASK_TEXT_MAPPING = {
     "clip_skip": "Clip Skip",
     "use_controlnet_model": "ControlNet model",
     "control_filter_to_apply": "ControlNet Filter",
+    "control_alpha": "ControlNet Strength",
     "use_vae_model": "VAE model",
     "sampler_name": "Sampler",
     "width": "Width",

ui/index.html

@@ -36,7 +36,7 @@
             <h1>
                 <img id="logo_img" src="/media/images/icon-512x512.png" >
                 Easy Diffusion
-                <small><span id="version">v3.0.7</span> <span id="updateBranchLabel"></span></small>
+                <small><span id="version">v3.0.9</span> <span id="updateBranchLabel"></span></small>
             </h1>
         </div>
         <div id="server-status">
@@ -239,6 +239,8 @@
                                 <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>
+                                <br/>
+                                <label for="controlnet_alpha_slider"><small>Strength:</small></label> <input id="controlnet_alpha_slider" name="controlnet_alpha_slider" class="editor-slider" value="10" type="range" min="0" max="10"> <input id="controlnet_alpha" name="controlnet_alpha" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)" inputmode="decimal">
                             </div>
                         </td>
                     </tr>

ui/media/js/auto-save.js

@@ -59,6 +59,7 @@ const SETTINGS_IDS_LIST = [
     "embedding-card-size-selector",
     "lora_model",
     "enable_vae_tiling",
+    "controlnet_alpha",
 ]
 
 const IGNORE_BY_DEFAULT = ["prompt"]

ui/media/js/dnd.js

@@ -309,10 +309,21 @@ const TASK_MAPPING = {
         readUI: () => controlImageFilterField.value,
         parse: (val) => val,
     },
+    control_alpha: {
+        name: "ControlNet Strength",
+        setUI: (control_alpha) => {
+            control_alpha = control_alpha || 1.0
+            controlAlphaField.value = control_alpha
+            updateControlAlphaSlider()
+        },
+        readUI: () => parseFloat(controlAlphaField.value),
+        parse: (val) => val === null ? 1.0 : parseFloat(val),
+    },
     use_lora_model: {
         name: "LoRA model",
         setUI: (use_lora_model) => {
             let modelPaths = []
+            use_lora_model = use_lora_model === null ? "" : use_lora_model
             use_lora_model = Array.isArray(use_lora_model) ? use_lora_model : [use_lora_model]
             use_lora_model.forEach((m) => {
                 if (m.includes("models\\lora\\")) {
@@ -529,6 +540,11 @@ function restoreTaskToUI(task, fieldsToSkip) {
         // listen for inpainter loading event, which happens AFTER the main image loads (which reloads the inpai
         controlImagePreview.src = task.reqBody.control_image
     }
+
+    if ("use_controlnet_model" in task.reqBody && task.reqBody.use_controlnet_model && !("control_alpha" in task.reqBody)) {
+        controlAlphaField.value = 1.0
+        updateControlAlphaSlider()
+    }
 }
 function readUI() {
     const reqBody = {}
@@ -587,6 +603,7 @@ const TASK_TEXT_MAPPING = {
     lora_alpha: "LoRA Strength",
     use_controlnet_model: "ControlNet model",
     control_filter_to_apply: "ControlNet Filter",
+    control_alpha: "ControlNet Strength",
     tiling: "Seamless Tiling",
 }
 function parseTaskFromText(str) {

ui/media/js/main.js

@@ -51,6 +51,10 @@ const taskConfigSetup = {
         preserve_init_image_color_profile: "Preserve Color Profile",
         strict_mask_border: "Strict Mask Border",
         use_controlnet_model: "ControlNet Model",
+        control_alpha: {
+            label: "ControlNet Strength",
+            visible: ({ reqBody }) => !!reqBody?.use_controlnet_model,
+        },
     },
     pluginTaskConfig: {},
     getCSSKey: (key) =>
@@ -99,6 +103,8 @@ 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 controlAlphaSlider = document.querySelector("#controlnet_alpha_slider")
+let controlAlphaField = document.querySelector("#controlnet_alpha")
 let applyColorCorrectionField = document.querySelector("#apply_color_correction")
 let strictMaskBorderField = document.querySelector("#strict_mask_border")
 let colorCorrectionSetting = document.querySelector("#apply_color_correction_setting")
@@ -1753,6 +1759,7 @@ function getCurrentUserRequest() {
     if (controlnetModelField.value !== "" && IMAGE_REGEX.test(controlImagePreview.src)) {
         newTask.reqBody.use_controlnet_model = controlnetModelField.value
         newTask.reqBody.control_image = controlImagePreview.src
+        newTask.reqBody.control_alpha = parseFloat(controlAlphaField.value)
         if (controlImageFilterField.value !== "") {
             newTask.reqBody.control_filter_to_apply = controlImageFilterField.value
         }
@@ -2374,6 +2381,27 @@ function updateHypernetworkStrengthContainer() {
 hypernetworkModelField.addEventListener("change", updateHypernetworkStrengthContainer)
 updateHypernetworkStrengthContainer()
 
+/********************* Controlnet Alpha **************************/
+function updateControlAlpha() {
+    controlAlphaField.value = controlAlphaSlider.value / 10
+    controlAlphaField.dispatchEvent(new Event("change"))
+}
+
+function updateControlAlphaSlider() {
+    if (controlAlphaField.value < 0) {
+        controlAlphaField.value = 0
+    } else if (controlAlphaField.value > 10) {
+        controlAlphaField.value = 10
+    }
+
+    controlAlphaSlider.value = controlAlphaField.value * 10
+    controlAlphaSlider.dispatchEvent(new Event("change"))
+}
+
+controlAlphaSlider.addEventListener("input", updateControlAlpha)
+controlAlphaField.addEventListener("input", updateControlAlphaSlider)
+updateControlAlpha()
+
 /********************* JPEG/WEBP Quality **********************/
 function updateOutputQuality() {
     outputQualityField.value = 0 | outputQualitySlider.value