fck off git

.ipynb_checkpoints/miniproject2-checkpoint.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# AI Miniproject 2 \n",
+    "\n",
+    "\n",
+    "Bla bla\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# stability.ai & Stable diffusion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import base64\n",
+    "import os\n",
+    "import requests\n",
+    "\n",
+    "engine_id = \"stable-diffusion-512-v2-1\"\n",
+    "api_host = 'https://api.stability.ai'\n",
+    "api_key = 'sk-v1z1pueYOHD2Bu83YL9undyzC54WW89eJkCAI79e4zLLeje1'\n",
+    "\n",
+    "response = requests.post(\n",
+    "    f\"{api_host}/v1/generation/{engine_id}/text-to-image\",\n",
+    "    headers={\n",
+    "        \"Content-Type\": \"application/json\",\n",
+    "        \"Accept\": \"application/json\",\n",
+    "        \"Authorization\": f\"Bearer {api_key}\"\n",
+    "    },\n",
+    "    json={\n",
+    "        \"text_prompts\": [\n",
+    "            {\n",
+    "                \"text\": \"A lighthouse on a cliff\"\n",
+    "            }\n",
+    "        ],\n",
+    "        \"cfg_scale\": 7,\n",
+    "        \"clip_guidance_preset\": \"FAST_BLUE\",\n",
+    "        \"height\": 512,\n",
+    "        \"width\": 512,\n",
+    "        \"samples\": 1,\n",
+    "        \"steps\": 30,\n",
+    "    },\n",
+    ")\n",
+    "\n",
+    "if response.status_code != 200:\n",
+    "    raise Exception(\"Non-200 response: \" + str(response.text))\n",
+    "\n",
+    "data = response.json()\n",
+    "\n",
+    "for i, image in enumerate(data[\"artifacts\"]):\n",
+    "    with open(f\"./out/v1_txt2img_{i}.png\", \"wb\") as f:\n",
+    "        f.write(base64.b64decode(image[\"base64\"]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

miniproject2.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# AI Miniproject 2 \n",
+    "\n",
+    "\n",
+    "Bla bla\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# stability.ai & Stable diffusion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import base64\n",
+    "import os\n",
+    "import requests\n",
+    "\n",
+    "engine_id = \"stable-diffusion-512-v2-1\"\n",
+    "api_host = 'https://api.stability.ai'\n",
+    "api_key = 'sk-v1z1pueYOHD2Bu83YL9undyzC54WW89eJkCAI79e4zLLeje1'\n",
+    "\n",
+    "response = requests.post(\n",
+    "    f\"{api_host}/v1/generation/{engine_id}/text-to-image\",\n",
+    "    headers={\n",
+    "        \"Content-Type\": \"application/json\",\n",
+    "        \"Accept\": \"application/json\",\n",
+    "        \"Authorization\": f\"Bearer {api_key}\"\n",
+    "    },\n",
+    "    json={\n",
+    "        \"text_prompts\": [\n",
+    "            {\n",
+    "                \"text\": \"A lighthouse on a cliff\"\n",
+    "            }\n",
+    "        ],\n",
+    "        \"cfg_scale\": 7,\n",
+    "        \"clip_guidance_preset\": \"FAST_BLUE\",\n",
+    "        \"height\": 512,\n",
+    "        \"width\": 512,\n",
+    "        \"samples\": 1,\n",
+    "        \"steps\": 30,\n",
+    "    },\n",
+    ")\n",
+    "\n",
+    "if response.status_code != 200:\n",
+    "    raise Exception(\"Non-200 response: \" + str(response.text))\n",
+    "\n",
+    "data = response.json()\n",
+    "\n",
+    "for i, image in enumerate(data[\"artifacts\"]):\n",
+    "    with open(f\"./out/v1_txt2img_{i}.png\", \"wb\") as f:\n",
+    "        f.write(base64.b64decode(image[\"base64\"]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}