Update check_modules.py

.github/FUNDING.yml

@@ -1,3 +1,4 @@
 # These are supported funding model platforms
 
 ko_fi: easydiffusion
+patreon: easydiffusion

CHANGES.md

@@ -17,8 +17,7 @@
 - **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.
+* 3.0.8 - 13 Mar 2024 - Update diffusers version to v0.26.3.
 * 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

@@ -15,16 +15,13 @@ 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"),
-    "setuptools": "69.5.1",
-    # "sdkit": "2.0.15.6", # checked later
-    # "diffusers": "0.21.4", # checked later
+    "sdkit": "2.0.18",
     "stable-diffusion-sdkit": "2.1.5",
     "rich": "12.6.0",
     "uvicorn": "0.19.0",
@@ -35,7 +32,7 @@ modules_to_check = {
     "python-multipart": "0.0.6",
     # "xformers": "0.0.16",
 }
-modules_to_log = ["torch", "torchvision", "sdkit", "stable-diffusion-sdkit", "diffusers"]
+modules_to_log = ["torch", "torchvision", "sdkit", "stable-diffusion-sdkit"]
 
 
 def version(module_name: str) -> str:
@@ -94,14 +91,6 @@ 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
@@ -121,114 +110,11 @@ def update_modules():
                 fail(module_name)
             else:
                 if version(module_name) != latest_version:
-                    print(
-                        f"WARNING! Tried to install {module_name}=={latest_version}, but the version is still {version(module_name)}!"
-                    )
-
-    # 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)}")
+                    print(f"WARNING! Tried to install {module_name}=={latest_version}, but the version is still {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))
+        if module_name in modules_to_log:
+            print(f"{module_name}: {version(module_name)}")
 
 
 ### utilities
@@ -291,10 +177,8 @@ Thanks!"""
     )
     exit(1)
 
-
 ### Launcher
 
-
 def get_config():
     config_directory = os.path.dirname(__file__)  # this will be "scripts"
     config_yaml = os.path.join(config_directory, "..", "config.yaml")
@@ -309,17 +193,15 @@ def get_config():
 
     if os.path.isfile(config_yaml):
         from ruamel.yaml import YAML
-
-        yaml = YAML(typ="safe")
-        with open(config_yaml, "r") as configfile:
+        yaml = YAML(typ='safe')
+        with open(config_yaml, 'r') as configfile:
             try:
                 config = yaml.load(configfile)
             except Exception as e:
                 print(e, file=sys.stderr)
     elif os.path.isfile(config_json):
         import json
-
-        with open(config_json, "r") as configfile:
+        with open(config_json, 'r') as configfile:
             try:
                 config = json.load(configfile)
             except Exception as e:
@@ -333,43 +215,43 @@ def get_config():
 def setup_amd_environment():
     if not os.access("/dev/kfd", os.W_OK):
         print(
-            "#########################################################################\n"
-            + "#           EasyDiffusion has no write access to /dev/kfd.              #\n"
-            + "#########################################################################\n"
-            + "\n"
-            + "Without this, the ROCm driver will probably not be able to initialize the GPU and EasyDiffusion will use the CPU for rendering.\n"
-            + "\n"
-            + "Follow the instructions on this site to configure the access:\n"
-            + "https://github.com/easydiffusion/easydiffusion/wiki/AMD-on-Linux#access-permissions\n"
-            + "\n"
+                  "#########################################################################\n"
+                + "#           EasyDiffusion has no write access to /dev/kfd.              #\n"
+                + "#########################################################################\n"
+                + "\n"
+                + "Without this, the ROCm driver will probably not be able to initialize the GPU and EasyDiffusion will use the CPU for rendering.\n"
+                + "\n"
+                + "Follow the instructions on this site to configure the access:\n"
+                + "https://github.com/easydiffusion/easydiffusion/wiki/AMD-on-Linux#access-permissions\n"
+                + "\n"
         )
 
     gpus = list(filter(lambda x: ("amdgpu" in x), open("/proc/bus/pci/devices", "r").readlines()))
-    gpus = [x.split("\t")[1].upper() for x in gpus]
-    gpus = [AMD_PCI_IDs[x] for x in gpus if x in AMD_PCI_IDs]
-    i = 0
-    supported_gpus = []
+    gpus = [ x.split("\t")[1].upper() for x in gpus ]
+    gpus = [ AMD_PCI_IDs[x] for x in gpus if x in AMD_PCI_IDs ]
+    i=0
+    supported_gpus=[]
     for gpu in gpus:
         print(f"Found AMD GPU {gpu}.")
         if gpu.startswith("Navi 1"):
             print("--- Applying Navi 1 settings")
-            os.environ["HSA_OVERRIDE_GFX_VERSION"] = "10.3.0"
-            os.environ["FORCE_FULL_PRECISION"] = "yes"
-            os.environ["HIP_VISIBLE_DEVICES"] = str(i)
+            os.environ["HSA_OVERRIDE_GFX_VERSION"]="10.3.0"
+            os.environ["FORCE_FULL_PRECISION"]="yes"
+            os.environ["HIP_VISIBLE_DEVICES"]=str(i)
             supported_gpus.append("Navi 1")
-        elif gpu.startswith("Navi 2"):
+        elif gpu.startswith("Navi 2"):    
             print("--- Applying Navi 2 settings")
-            os.environ["HSA_OVERRIDE_GFX_VERSION"] = "10.3.0"
-            os.environ["HIP_VISIBLE_DEVICES"] = str(i)
+            os.environ["HSA_OVERRIDE_GFX_VERSION"]="10.3.0"
+            os.environ["HIP_VISIBLE_DEVICES"]=str(i)
             supported_gpus.append("Navi 2")
         elif gpu.startswith("Navi 3"):
             print("--- Applying Navi 3 settings")
-            os.environ["HSA_OVERRIDE_GFX_VERSION"] = "11.0.0"
-            os.environ["HIP_VISIBLE_DEVICES"] = str(i)
+            os.environ["HSA_OVERRIDE_GFX_VERSION"]="11.0.0"
+            os.environ["HIP_VISIBLE_DEVICES"]=str(i)
             supported_gpus.append("Navi 3")
         else:
             print("--- This GPU is probably not supported by ROCm\n")
-        i += 1
+        i+=1
     return supported_gpus
 
 
@@ -378,7 +260,7 @@ def launch_uvicorn():
 
     pprint(config)
 
-    with open("scripts/install_status.txt", "a") as f:
+    with open("scripts/install_status.txt","a") as f:
         f.write("sd_weights_downloaded\n")
         f.write("sd_install_complete\n")
 
@@ -386,9 +268,9 @@ def launch_uvicorn():
 
     os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
     if os_name == "Windows":
-        os.environ["PYTHONPATH"] = str(Path(os.environ["INSTALL_ENV_DIR"], "lib", "site-packages"))
+        os.environ["PYTHONPATH"] = str(Path( os.environ["INSTALL_ENV_DIR"], "lib", "site-packages"))
     else:
-        os.environ["PYTHONPATH"] = str(Path(os.environ["INSTALL_ENV_DIR"], "lib", "python3.8", "site-packages"))
+        os.environ["PYTHONPATH"] = str(Path( os.environ["INSTALL_ENV_DIR"], "lib", "python3.8", "site-packages"))
     os.environ["SD_UI_PATH"] = str(Path(Path.cwd(), "ui"))
 
     print(f"PYTHONPATH={os.environ['PYTHONPATH']}")
@@ -415,18 +297,7 @@ def launch_uvicorn():
         setup_amd_environment()
 
     print("\nLaunching uvicorn\n")
-
-    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,
-    )
-
+    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')
 
 ### Start
 
@@ -1231,5 +1102,5 @@ AMD_PCI_IDs = {
 
 update_modules()
 
-if len(sys.argv) > 1 and sys.argv[1] == "--launch-uvicorn":
+if len(sys.argv) > 1 and sys.argv[1]=="--launch-uvicorn":
     launch_uvicorn()

ui/easydiffusion/device_manager.py

@@ -243,8 +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"
+            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()
         elif platform.system() == "Linux":

ui/easydiffusion/model_manager.py

@@ -37,7 +37,7 @@ MODEL_EXTENSIONS = {
 }
 DEFAULT_MODELS = {
     "stable-diffusion": [
-        {"file_name": "sd-v1-4.ckpt", "model_id": "1.4"},
+        {"file_name": "sd-v1-5.safetensors", "model_id": "1.5-pruned-emaonly-fp16"},
     ],
     "gfpgan": [
         {"file_name": "GFPGANv1.4.pth", "model_id": "1.4"},

ui/easydiffusion/utils/save_utils.py

@@ -31,7 +31,6 @@ 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

@@ -35,7 +35,7 @@
             <h1>
                 <img id="logo_img" src="/media/images/icon-512x512.png" >
                 Easy Diffusion
-                <small><span id="version">v3.0.9</span> <span id="updateBranchLabel"></span></small>
+                <small><span id="version">v3.0.8</span> <span id="updateBranchLabel"></span></small>
             </h1>
         </div>
         <div id="server-status">
@@ -235,8 +235,6 @@
                                 <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>
@@ -268,7 +266,7 @@
                             <option value="unipc_tu_2" class="k_diffusion-only">UniPC TU 2</option>
                             <option value="unipc_tq" class="k_diffusion-only">UniPC TQ</option>
                         </select>
-                        <a href="https://github.com/easydiffusion/easydiffusion/wiki/Samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about samplers</span></i></a>
+                        <a href="https://github.com/easydiffusion/easydiffusion/wiki/How-to-Use#samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about samplers</span></i></a>
                     </td></tr>
                     <tr class="pl-5"><td><label>Image Size: </label></td><td id="image-size-options">
                         <select id="width" name="width" value="512">

ui/media/js/auto-save.js

@@ -57,7 +57,6 @@ 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

@@ -309,21 +309,10 @@ 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\\")) {
@@ -540,11 +529,6 @@ 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 = {}
@@ -603,7 +587,6 @@ 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

@@ -51,10 +51,6 @@ 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) =>
@@ -103,8 +99,6 @@ 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")
@@ -1401,7 +1395,6 @@ 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
         }
@@ -2022,27 +2015,6 @@ 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