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\n {\n

\n }\n

,\n ),\n );\n }\n\n return new Response(\n render(\n \n \n Movie Real\n \n \n \n \n \n \n

Movie Real

\n \n

\n Search the cinematic universe\n

\n Face\n \n

\n Prompt\n \n

\n\n \n

\n \n\n

\n \n ,\n ),\n {\n headers: {\n \"Content-Type\": \"text/html; charset=utf-8\",\n },\n },\n );\n console.log(22222222);\n}","/** @jsxImportSource https://esm.sh/preact */\nimport { encode } from \"https://deno.land/std@0.107.0/encoding/base64.ts\";\nimport { render } from \"npm:preact-render-to-string\";\nimport Replicate from \"npm:replicate\";\n\nconst replicate = new Replicate({\n auth: Deno.env.get(\"REPLICATE_API_TOKEN\"),\n});\n\nexport default async function(req: Request) {\n if (req.method === \"POST\") {\n const formData = await req.formData();\n const image = formData.get(\"image\");\n const textPrompt = formData.get(\"textPrompt\");\n // Run generative model\n const generatedImage = await replicate.run(\n \"adirik/realvisxl-v3.0-turbo:6e941e7fe46955afc031f35e84312a792d546b0f434f9008d457eb9deb24575c\",\n {\n input: {\n prompt: textPrompt + \", cinematic movie still 35mm, film grain\",\n num_inference_steps: 20,\n guidance_scale: 5,\n height: 768,\n width: 1304, // this is 16x9\n },\n },\n );\n\n // Convert the source image to data URL\n const source = `data:${image.type};base64,${encode(new Uint8Array(await image.arrayBuffer()))}`;\n\n // Run faceswap model\n const output = await replicate.run(\n \"lucataco/faceswap:9a4298548422074c3f57258c5d544497314ae4112df80d116f0d2109e843d20d\",\n {\n input: {\n swap_image: source,\n target_image: generatedImage[0],\n },\n },\n );\n\n const result = output;\n console.log(22222222);\n\n return new Response(\n render(\n

\n {\n

\n }\n

,\n ),\n );\n }\n\n return new Response(\n render(\n \n \n Movie Real\n \n \n \n \n \n \n

Movie Real

\n \n

\n Search the cinematic universe\n

\n Face\n \n

\n Prompt\n \n

\n\n \n

\n \n\n

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Diff · v57