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insightface\n", + "!pip install onnxruntime\n", + "!git clone https://github.com/InstantID/InstantID.git\n", + "%cd InstantID\n", + "!pip install gdown" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 236, + "referenced_widgets": [ + "2e9f28f9fea448818eb5dcdd0e18fbdc", + "3324c70d6e9e499aba28a2111681d0d8", + "7f3734999e9944589c65611d871c5d00", + "31420ae4ac864088a6c0f4989c2a550f", + "983c2492967248bab05d02ea8a1d59e3", + "7bc326963c0e46daa70be7e4dbb3da30", + "eb0c06067faa4462b6fe98701d0cd189", + "a342a5e370b645279864eace41cae666", + "5087b58f77614dbb8624192aae456d11", + "971c88bd6eed4278958b95700adc2967", + "b0567d501ec7455cb9fc0a70cb8fa0ef", + "2aa02d48d1474df4bbb04bd086179831", + "a65a49d6a2234fe1a368f82034ec0f7c", + "99fb305fcc064f4794203c1c2dd5360d", + "c89b9da680144b45bed3eb9549a73a48", + "3101bf6df10a4c5fb35d8aede369790c", + "aaabf55935794baf962db282e81ecaea", + 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in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", + "You will be able to reuse this secret in all of your notebooks.\n", + "Please note that authentication is recommended but still optional to access public models or datasets.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2e9f28f9fea448818eb5dcdd0e18fbdc", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "ControlNetModel/config.json: 0%| | 0.00/1.38k [00:00" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# load an image\n", + "face_image = load_image(\"/content/InstantID/examples/yann-lecun_resize.jpg\")\n", + "\n", + "# prepare face emb\n", + "face_info = app.get(cv2.cvtColor(np.array(face_image), cv2.COLOR_RGB2BGR))\n", + "face_info = sorted(face_info, key=lambda x:(x['bbox'][2]-x['bbox'][0])*x['bbox'][3]-x['bbox'][1])[-1] # only use the maximum face\n", + "face_emb = face_info['embedding']\n", + "face_kps = draw_kps(face_image, face_info['kps'])\n", + "\n", + "# prompt\n", + "prompt = \"cinematic film still a man sitting on bench . shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy\"\n", + "negative_prompt = \"anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured\"\n", + "\n", + "# generate image\n", + "pipe.set_ip_adapter_scale(0.2)\n", + "image = pipe(\n", + " prompt,\n", + " image_embeds=face_emb,\n", + " image=face_kps,\n", + " controlnet_conditioning_scale=0.6,\n", + ").images[0]\n", + "image" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "gpuType": "T4", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": 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