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Runtime error
Runtime error
add extra options to img2img
Browse files- app-img2img.py +9 -12
- img2img/index.html +103 -22
app-img2img.py
CHANGED
@@ -76,9 +76,9 @@ pipe.unet.to(memory_format=torch.channels_last)
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if psutil.virtual_memory().total < 64 * 1024**3:
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pipe.enable_attention_slicing()
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if not mps_available and not xpu_available:
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compel_proc = Compel(
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tokenizer=pipe.tokenizer,
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@@ -89,30 +89,27 @@ user_queue_map = {}
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class InputParams(BaseModel):
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prompt: str
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seed: int = 2159232
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guidance_scale: float = 8.0
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strength: float = 0.5
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width: int = WIDTH
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height: int = HEIGHT
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def predict(
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input_image: Image.Image, params: InputParams, prompt_embeds: torch.Tensor = None
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):
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generator = torch.manual_seed(params.seed)
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# Can be set to 1~50 steps. LCM support fast inference even <= 4 steps. Recommend: 1~8 steps.
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num_inference_steps = 4
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results = pipe(
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prompt_embeds=prompt_embeds,
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generator=generator,
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image=input_image,
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strength=params.strength,
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num_inference_steps=
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guidance_scale=params.guidance_scale,
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width=params.width,
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height=params.height,
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original_inference_steps=
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output_type="pil",
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)
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nsfw_content_detected = (
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if psutil.virtual_memory().total < 64 * 1024**3:
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pipe.enable_attention_slicing()
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# if not mps_available and not xpu_available:
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# pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
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# pipe(prompt="warmup", image=[Image.new("RGB", (512, 512))])
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compel_proc = Compel(
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tokenizer=pipe.tokenizer,
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class InputParams(BaseModel):
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seed: int = 2159232
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prompt: str
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guidance_scale: float = 8.0
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strength: float = 0.5
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steps: int = 4
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lcm_steps: int = 50
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width: int = WIDTH
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height: int = HEIGHT
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def predict(input_image: Image.Image, params: InputParams, prompt_embeds: torch.Tensor = None):
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generator = torch.manual_seed(params.seed)
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results = pipe(
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prompt_embeds=prompt_embeds,
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generator=generator,
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image=input_image,
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strength=params.strength,
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num_inference_steps=params.steps,
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guidance_scale=params.guidance_scale,
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width=params.width,
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height=params.height,
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original_inference_steps=params.lcm_steps,
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output_type="pil",
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)
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nsfw_content_detected = (
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img2img/index.html
CHANGED
@@ -15,13 +15,13 @@
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}
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</style>
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<script type="module">
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const startBtn = document.querySelector("#start");
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const stopBtn = document.querySelector("#stop");
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const videoEl = document.querySelector("#webcam");
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@@ -29,8 +29,9 @@
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const queueSizeEl = document.querySelector("#queue_size");
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const errorEl = document.querySelector("#error");
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const snapBtn = document.querySelector("#snap");
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function LCMLive(webcamVideo, liveImage
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let websocket;
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async function start() {
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@@ -72,30 +73,73 @@
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websocket = socket;
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})
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}
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async function videoTimeUpdateHandler() {
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const canvas = new OffscreenCanvas(WIDTH, HEIGHT);
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const videoW = webcamVideo.videoWidth;
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const videoH = webcamVideo.videoHeight;
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const ctx = canvas.getContext("2d");
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ctx.drawImage(webcamVideo, videoW / 2 - WIDTH / 2, videoH / 2 - HEIGHT / 2, WIDTH, HEIGHT, 0, 0, canvas.width, canvas.height);
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const blob = await canvas.convertToBlob({ type: "image/jpeg", quality: 1 });
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websocket.send(blob);
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websocket.send(JSON.stringify({
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"seed":
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"prompt":
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"guidance_scale":
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"strength":
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}));
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}
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function initVideoStream(userId) {
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liveImage.src = `/stream/${userId}`;
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const constraints = {
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audio: false,
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video: { width:
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};
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navigator.mediaDevices
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.getUserMedia(constraints)
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@@ -117,6 +161,7 @@
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mediaStream.getTracks().forEach((track) => track.stop());
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});
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webcamVideo.removeEventListener("timeupdate", videoTimeUpdateHandler);
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webcamVideo.srcObject = null;
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}
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return {
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@@ -147,7 +192,7 @@
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const exif = {};
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const gps = {};
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zeroth[piexif.ImageIFD.Make] = "LCM Image-to-Image";
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zeroth[piexif.ImageIFD.ImageDescription] = `prompt: ${
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zeroth[piexif.ImageIFD.Software] = "https://github.com/radames/Real-Time-Latent-Consistency-Model";
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exif[piexif.ExifIFD.DateTimeOriginal] = new Date().toISOString();
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@@ -173,7 +218,7 @@
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}
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const lcmLive = LCMLive(videoEl, imageEl
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startBtn.addEventListener("click", async () => {
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try {
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startBtn.disabled = true;
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@@ -249,18 +294,38 @@
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<div class="">
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<details>
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<summary class="font-medium cursor-pointer">Advanced Options</summary>
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<div class="grid grid-cols-3
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<label class="text-sm font-medium" for="guidance-scale">Guidance Scale
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</label>
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<input type="range" id="guidance-scale" name="guidance-scale" min="
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value="8.0" oninput="this.nextElementSibling.value = Number(this.value).toFixed(2)">
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<output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
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8.0</output>
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<label class="text-sm font-medium" for="strength">Strength</label>
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<input type="range" id="strength" name="strength" min="0.
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oninput="this.nextElementSibling.value = Number(this.value).toFixed(2)">
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<output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
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0.5</output>
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<label class="text-sm font-medium" for="seed">Seed</label>
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<input type="number" id="seed" name="seed" value="299792458"
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class="font-light border border-gray-700 text-right rounded-md p-2 dark:text-black">
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@@ -269,6 +334,22 @@
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class="button">
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Rand
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</button>
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</div>
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</details>
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</div>
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}
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</style>
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<script type="module">
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const getValue = (id) => {
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const el = document.querySelector(`${id}`)
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if (el.type === "checkbox")
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return el.checked;
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return el.value;
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}
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const startBtn = document.querySelector("#start");
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const stopBtn = document.querySelector("#stop");
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const videoEl = document.querySelector("#webcam");
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const queueSizeEl = document.querySelector("#queue_size");
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const errorEl = document.querySelector("#error");
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const snapBtn = document.querySelector("#snap");
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const webcamsEl = document.querySelector("#webcams");
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function LCMLive(webcamVideo, liveImage) {
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let websocket;
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async function start() {
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websocket = socket;
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})
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}
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function switchCamera() {
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const constraints = {
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audio: false,
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video: { width: 1024, height: 1024, deviceId: mediaDevices[webcamsEl.value].deviceId }
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};
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navigator.mediaDevices
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.getUserMedia(constraints)
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.then((mediaStream) => {
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webcamVideo.removeEventListener("timeupdate", videoTimeUpdateHandler);
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webcamVideo.srcObject = mediaStream;
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webcamVideo.onloadedmetadata = () => {
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webcamVideo.play();
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webcamVideo.addEventListener("timeupdate", videoTimeUpdateHandler);
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};
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})
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.catch((err) => {
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console.error(`${err.name}: ${err.message}`);
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});
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}
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async function videoTimeUpdateHandler() {
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const dimension = getValue("input[name=dimension]:checked");
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const [WIDTH, HEIGHT] = JSON.parse(dimension);
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const canvas = new OffscreenCanvas(WIDTH, HEIGHT);
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const videoW = webcamVideo.videoWidth;
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const videoH = webcamVideo.videoHeight;
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const aspectRatio = WIDTH / HEIGHT;
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const ctx = canvas.getContext("2d");
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ctx.drawImage(webcamVideo, videoW / 2 - videoH * aspectRatio / 2, 0, videoH * aspectRatio, videoH, 0, 0, WIDTH, HEIGHT)
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const blob = await canvas.convertToBlob({ type: "image/jpeg", quality: 1 });
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websocket.send(blob);
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websocket.send(JSON.stringify({
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"seed": getValue("#seed"),
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"prompt": getValue("#prompt"),
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"guidance_scale": getValue("#guidance-scale"),
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"strength": getValue("#strength"),
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"steps": getValue("#steps"),
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"lcm_steps": getValue("#lcm_steps"),
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"width": WIDTH,
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"height": HEIGHT,
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}));
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}
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let mediaDevices = [];
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async function initVideoStream(userId) {
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liveImage.src = `/stream/${userId}`;
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await navigator.mediaDevices.enumerateDevices()
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.then(devices => {
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const cameras = devices.filter(device => device.kind === 'videoinput');
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mediaDevices = cameras;
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webcamsEl.innerHTML = "";
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cameras.forEach((camera, index) => {
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const option = document.createElement("option");
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option.value = index;
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option.innerText = camera.label;
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webcamsEl.appendChild(option);
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option.selected = index === 0;
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});
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webcamsEl.addEventListener("change", switchCamera);
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})
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.catch(err => {
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console.error(err);
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});
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const constraints = {
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audio: false,
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video: { width: 1024, height: 1024, deviceId: mediaDevices[0].deviceId }
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};
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navigator.mediaDevices
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.getUserMedia(constraints)
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mediaStream.getTracks().forEach((track) => track.stop());
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});
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webcamVideo.removeEventListener("timeupdate", videoTimeUpdateHandler);
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webcamsEl.removeEventListener("change", switchCamera);
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webcamVideo.srcObject = null;
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}
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return {
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const exif = {};
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const gps = {};
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zeroth[piexif.ImageIFD.Make] = "LCM Image-to-Image";
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zeroth[piexif.ImageIFD.ImageDescription] = `prompt: ${getValue("#prompt")} | seed: ${getValue("#seed")} | guidance_scale: ${getValue("#guidance-scale")} | strength: ${getValue("#strength")} | lcm_steps: ${getValue("#lcm_steps")} | steps: ${getValue("#steps")}`;
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zeroth[piexif.ImageIFD.Software] = "https://github.com/radames/Real-Time-Latent-Consistency-Model";
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exif[piexif.ExifIFD.DateTimeOriginal] = new Date().toISOString();
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}
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const lcmLive = LCMLive(videoEl, imageEl);
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startBtn.addEventListener("click", async () => {
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try {
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startBtn.disabled = true;
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<div class="">
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<details>
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<summary class="font-medium cursor-pointer">Advanced Options</summary>
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<div class="grid grid-cols-3 sm:grid-cols-6 items-center gap-3 py-3">
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<label for="webcams" class="text-sm font-medium">Camera Options: </label>
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<select id="webcams" class="text-sm border-2 border-gray-500 rounded-md font-light dark:text-black">
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</select>
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<div></div>
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<label class="text-sm font-medium " for="steps">Inference Steps
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</label>
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<input type="range" id="steps" name="steps" min="1" max="20" value="4"
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oninput="this.nextElementSibling.value = Number(this.value)">
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<output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
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4</output>
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<!-- -->
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<label class="text-sm font-medium" for="lcm_steps">LCM Inference Steps
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</label>
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<input type="range" id="lcm_steps" name="lcm_steps" min="2" max="60" value="50"
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oninput="this.nextElementSibling.value = Number(this.value)">
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<output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
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50</output>
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<!-- -->
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<label class="text-sm font-medium" for="guidance-scale">Guidance Scale
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</label>
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<input type="range" id="guidance-scale" name="guidance-scale" min="0" max="30" step="0.001"
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value="8.0" oninput="this.nextElementSibling.value = Number(this.value).toFixed(2)">
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<output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
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8.0</output>
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<!-- -->
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<label class="text-sm font-medium" for="strength">Strength</label>
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<input type="range" id="strength" name="strength" min="0.1" max="1" step="0.001" value="0.50"
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oninput="this.nextElementSibling.value = Number(this.value).toFixed(2)">
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<output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
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0.5</output>
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<!-- -->
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<label class="text-sm font-medium" for="seed">Seed</label>
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<input type="number" id="seed" name="seed" value="299792458"
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class="font-light border border-gray-700 text-right rounded-md p-2 dark:text-black">
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class="button">
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Rand
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</button>
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<!-- -->
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<!-- -->
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<label class="text-sm font-medium" for="dimension">Image Dimensions</label>
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<div class="col-span-2 flex gap-2">
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<div class="flex gap-1">
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<input type="radio" id="dimension512" name="dimension" value="[512,512]" checked
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class="cursor-pointer">
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<label for="dimension512" class="text-sm cursor-pointer">512x512</label>
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</div>
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<div class="flex gap-1">
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<input type="radio" id="dimension768" name="dimension" value="[768,768]"
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lass="cursor-pointer">
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<label for="dimension768" class="text-sm cursor-pointer">768x768</label>
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</div>
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</div>
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<!-- -->
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</div>
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</details>
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</div>
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