diff --git a/README.md b/README.md index a842723..cf8d0df 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,17 @@ https://www.sqlitetutorial.net/sqlite-sample-database/ # Tools -## Assistants Playground +## Scenario API + +### IP Adapters in Game Design + +https://help.scenario.com/integrating-ip-adapters-for-game-development + +### LoRA Character Bases in Game Design + +https://help.scenario.com/integrating-lora-character-bases-in-game-design + +## Open AI Assistants Playground https://platform.openai.com/assistants diff --git a/Scenario_GG_Image_Generation_API.ipynb b/Scenario_GG_Image_Generation_API.ipynb new file mode 100644 index 0000000..2bf1ccc --- /dev/null +++ b/Scenario_GG_Image_Generation_API.ipynb @@ -0,0 +1,600 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "id": "cQKbozxw9QD7" + }, + "outputs": [], + "source": [ + "import base64\n", + "from google.colab import userdata\n", + "import requests\n", + "import time\n", + "from IPython.display import Image, display\n", + "\n", + "\n", + "key = userdata.get('SCENARIO_API_KEY')\n", + "secret = userdata.get('SCENARIO_API_SECRET')\n", + "auth_header = \"Basic \" + base64.b64encode(f\"{key}:{secret}\".encode('ascii')).decode('ascii')\n", + "\n", + "# Set the base URL\n", + "base_url = 'https://api.cloud.scenario.com/v1'\n", + "model_id = 'WMFVfL6ASISizG1T7X2NNw' # It's one of our signature public models\n", + "\n", + "# Set the authentication header\n", + "headers = {\n", + " 'accept': 'application/json',\n", + " 'Authorization': auth_header\n", + "}\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Oia7rImZDcHx" + }, + "source": [ + "# Run a txt2img inference and retrieve results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "yRxZha0V-tbn" + }, + "outputs": [], + "source": [ + "\n", + "\n", + "# Make a POST request to create an inference\n", + "response = requests.post(f'{base_url}/models/{model_id}/inferences', json={\n", + " 'parameters': {\n", + " 'type': 'txt2img',\n", + " 'prompt':\n", + " 'close up portrait of a sci-fi character in red armor with cyber helmet, lights on cyber mask, full armor, insulated armor, angry, active pose, strong warrior, weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting',\n", + " 'numInferenceSteps': 30,\n", + " 'numSamples': 2,\n", + " 'guidance': 7.5,\n", + " 'width': 512,\n", + " 'height': 512,\n", + " 'negativePrompt': 'ugly, bad, low quality, blurry',\n", + " }\n", + "}, headers=headers)\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "def check_progress_get_results(response):\n", + "\n", + " # Check if the request was successful\n", + " if response.status_code == 200:\n", + " data = response.json()\n", + " print(data)\n", + " inference_id = data['inference']['id']\n", + "\n", + " # Function to poll the inference status\n", + " def poll_inference_status(model_id, inference_id):\n", + " status = ''\n", + " while status not in ['succeeded', 'failed']:\n", + " # Fetch the inference details\n", + " inference_response = requests.get(f'{base_url}/models/{model_id}/inferences/{inference_id}', headers=headers)\n", + " inference_data = inference_response.json()\n", + " print(inference_data)\n", + "\n", + " # Safely access nested data with .get()\n", + " inference_info = inference_data.get('inference', {})\n", + " status = inference_info.get('status')\n", + " print(f'Inference status: {status}')\n", + "\n", + " # Wait for a certain interval before polling again\n", + " time.sleep(5) # Polling every 5 seconds\n", + "\n", + " # Handle the final status\n", + " if status == 'succeeded':\n", + " print('Inference succeeded!')\n", + " print(inference_data) # Print inference data\n", + "\n", + "\n", + " # Access the images list\n", + " images = inference_data['inference']['images']\n", + " if images:\n", + " for img in images:\n", + " display(Image(url=img['url']))\n", + "\n", + "\n", + " else:\n", + " print('Inference failed!')\n", + " print(inference_data) # Print inference data\n", + "\n", + " # Start polling the inference status\n", + " poll_inference_status(model_id, inference_id)\n", + "\n", + "\n", + "\n", + " else:\n", + " print(f'Error: {response.status_code}')\n", + "\n", + " # Try to print the response content to see if there's an error message\n", + " try:\n", + " error_message = response.json().get('message', response.text)\n", + " except ValueError: # Includes simplejson.decoder.JSONDecodeError\n", + " error_message = response.text\n", + " print(f\"Error message: {error_message}\")" + ], + "metadata": { + "id": "t1E9Pi6id_H1" + }, + "execution_count": 2, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "\n", + "def check_progress_set_lcm(response, prompt='red hair'):\n", + "\n", + " # Check if the request was successful\n", + " if response.status_code == 200:\n", + " data = response.json()\n", + " print(data)\n", + " inference_id = data['inference']['id']\n", + "\n", + " # Function to poll the inference status\n", + " def poll_inference_status(model_id, inference_id):\n", + " status = ''\n", + " while status not in ['succeeded', 'failed']:\n", + " # Fetch the inference details\n", + " inference_response = requests.get(f'{base_url}/models/{model_id}/inferences/{inference_id}', headers=headers)\n", + " inference_data = inference_response.json()\n", + " print(inference_data)\n", + "\n", + " # Safely access nested data with .get()\n", + " inference_info = inference_data.get('inference', {})\n", + " status = inference_info.get('status')\n", + " print(f'Inference status: {status}')\n", + "\n", + " # Wait for a certain interval before polling again\n", + " time.sleep(5) # Polling every 5 seconds\n", + "\n", + " # Handle the final status\n", + " if status == 'succeeded':\n", + " print('Inference succeeded!')\n", + " print(inference_data) # Print inference data\n", + "\n", + "\n", + "\n", + " # Make a POST request to create another inference\n", + " lcm_response = requests.post(f\"{base_url}/models/{model_id}/inferences\", headers={\n", + " **headers,\n", + " 'Content-Type': 'application/json'\n", + " }, json={\n", + " 'parameters': {\n", + " 'type': 'txt2img_ip_adapter',\n", + " 'ipAdapterScale': 0.5,\n", + " 'ipAdapterImageId': inference_data['inference']['images'][0]['id'],\n", + " 'prompt': prompt,\n", + " 'numInferenceSteps': 30,\n", + " 'numSamples': 2,\n", + " 'guidance': 1.5,\n", + " 'width': 1024,\n", + " 'height': 1024,\n", + " 'negativePrompt': 'ugly, bad, low quality, blurry',\n", + " 'scheduler': 'LCMScheduler',\n", + " }\n", + " })\n", + "\n", + " check_progress_get_results(lcm_response)\n", + "\n", + "\n", + "\n", + " else:\n", + " print('Inference failed!')\n", + " print(inference_data) # Print inference data\n", + "\n", + " # Start polling the inference status\n", + " poll_inference_status(model_id, inference_id)\n", + "\n", + "\n", + "\n", + " else:\n", + " print(f'Error: {response.status_code}')\n", + "\n", + " # Try to print the response content to see if there's an error message\n", + " try:\n", + " error_message = response.json().get('message', response.text)\n", + " except ValueError: # Includes simplejson.decoder.JSONDecodeError\n", + " error_message = response.text\n", + " print(f\"Error message: {error_message}\")" + ], + "metadata": { + "id": "LTR2iv_feAF_" + }, + "execution_count": 3, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "# Generate base64 image url" + ], + "metadata": { + "id": "d0GtfL_Ronph" + } + }, + { + "cell_type": "code", + "source": [ + "import base64\n", + "\n", + "def make_data_url(filename):\n", + " with open(filename, 'rb') as fin:\n", + " contents = fin.read()\n", + " data_url = f'data:image/png;base64,{base64.b64encode(contents).decode()}'\n", + " return data_url\n", + "\n", + "import requests\n", + "\n", + "def make_data_url_from_url(image_url):\n", + " # Fetch the image over HTTP\n", + " response = requests.get(image_url)\n", + "\n", + " # Ensure the request was successful\n", + " if response.status_code == 200:\n", + " # Convert the response content (which is the image in binary format)\n", + " # to a base64-encoded data URL\n", + " data_url = f'data:image/png;base64,{base64.b64encode(response.content).decode()}'\n", + " return data_url\n", + " else:\n", + " # Handle errors or unsuccessful status codes\n", + " raise Exception(f\"Failed to retrieve image. Status code: {response.status_code}\")\n" + ], + "metadata": { + "id": "QhAXJRYeoril" + }, + "execution_count": 19, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from logging import error\n", + "import random\n", + "urls = [\n", + " 'https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/a3be3290-de9b-48ee-d46b-8ee71b369000/width=450/04881-1945394030-cf6.5-Euler%20a-s20-a9263745.jpeg'\n", + " 'https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/6a93704d-1e19-4297-ab79-92423c122260/width=450/00041-2334832487.jpeg'\n", + " 'https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRZQj-VWbPuMFWq3HMkKPaPF_b9zQYVup80mxES7z6J8A&s',\n", + " 'https://civitai-image-uploads.5ac0637cfd0766c97916cefa3764fbdf.r2.cloudflarestorage.com/a21ebf09-3fae-4cbd-7484-7b647f9f5f00?X-Amz-Expires=86400&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=c771abc02017f796f020b37d604550ae/20240401/us-east-1/s3/aws4_request&X-Amz-Date=20240401T221711Z&X-Amz-SignedHeaders=host&X-Amz-Signature=9904a440ee95d61ce7b2cdbfbdab877bd2c98e15bab46edc83b4aad5ea3a91af'\n", + "]\n", + "url = random.choice(urls)\n", + "print(url)\n", + "try:\n", + " base64_data_url = userdata.get('base64_depthmap')\n", + "except userdata.SecretNotFoundError:\n", + " base64_data_url = make_data_url_from_url(url)\n", + "\n", + "display(Image(url=base64_data_url))\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 509 + }, + "id": "ba2NHokeossj", + "outputId": "05c9e938-cd6a-4d67-f07f-8b7175016b78" + }, + "execution_count": 59, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/a3be3290-de9b-48ee-d46b-8ee71b369000/width=450/04881-1945394030-cf6.5-Euler%20a-s20-a9263745.jpeghttps://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/6a93704d-1e19-4297-ab79-92423c122260/width=450/00041-2334832487.jpeghttps://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRZQj-VWbPuMFWq3HMkKPaPF_b9zQYVup80mxES7z6J8A&s\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MK66uHAFEHhI" + }, + "source": [ + "With a ControlNet model, you can provide an additional control image to condition and control generation. For example, if you provide a depth map, the ControlNet model generates an image that’ll preserve the spatial information from the depth map. It is a more flexible and accurate way to control the image generation process.\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "PR_JwrijEIVJ", + "outputId": "d471e0da-e578-48aa-ef5b-d8f78383bd8f" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "{'inference': {'id': 'inf_dTXDbskJ57wm1EbdyZLLqHvC', 'userId': '8abf83b97f13c13ecb5090739c2a3461', 'ownerId': 'team_5XP3979oXCXmbtCbFpa6phBv', 'authorId': '8abf83b97f13c13ecb5090739c2a3461', 'modelId': 'WMFVfL6ASISizG1T7X2NNw', 'createdAt': '2024-04-01T22:22:44.083Z', 'parameters': {'type': 'controlnet', 'prompt': 'close up portrait of a sci-fi character in red armor with cyber helmet, lights on cyber mask, full armor, insulated armor, angry, active pose, strong warrior, weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting', 'negativePrompt': 'ugly, bad, low quality, blurry', 'numSamples': 2, 'intermediateImages': False, 'guidance': 7.5, 'numInferenceSteps': 30, 'width': 512, 'height': 512, 'hideResults': False, 'tokenMerging': 0, 'qualityBoost': False, 'modality': 'depth:0.9', 'disableModalityDetection': False, 'image': 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bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting'}, 'creativeUnitsCost': 2.4}\n", + "{'inference': {'id': 'inf_dTXDbskJ57wm1EbdyZLLqHvC', 'userId': '8abf83b97f13c13ecb5090739c2a3461', 'ownerId': 'team_5XP3979oXCXmbtCbFpa6phBv', 'authorId': '8abf83b97f13c13ecb5090739c2a3461', 'modelId': 'WMFVfL6ASISizG1T7X2NNw', 'createdAt': '2024-04-01T22:22:44.083Z', 'parameters': {'modality': 'depth:0.9', 'qualityBoost': False, 'hideResults': False, 'type': 'controlnet', 'negativePrompt': 'ugly, bad, low quality, blurry', 'intermediateImages': False, 'guidance': 7.5, 'numInferenceSteps': 30, 'disableModalityDetection': False, 'numSamples': 2, 'tokenMerging': 0, 'width': 512, 'prompt': 'close up portrait of a sci-fi character in red armor with cyber helmet, 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weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting'}}\n", + "Inference status: model-loading\n", + "{'inference': {'id': 'inf_dTXDbskJ57wm1EbdyZLLqHvC', 'userId': '8abf83b97f13c13ecb5090739c2a3461', 'ownerId': 'team_5XP3979oXCXmbtCbFpa6phBv', 'authorId': '8abf83b97f13c13ecb5090739c2a3461', 'modelId': 'WMFVfL6ASISizG1T7X2NNw', 'createdAt': '2024-04-01T22:22:44.083Z', 'parameters': {'modality': 'depth:0.9', 'qualityBoost': False, 'hideResults': False, 'type': 'controlnet', 'negativePrompt': 'ugly, bad, low quality, blurry', 'intermediateImages': False, 'guidance': 7.5, 'numInferenceSteps': 30, 'disableModalityDetection': False, 'numSamples': 2, 'tokenMerging': 0, 'width': 512, 'prompt': 'close up portrait of a sci-fi character in red armor with cyber helmet, lights on cyber mask, full armor, insulated armor, angry, active pose, strong warrior, weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting', 'height': 512, 'image': 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weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting'}}\n", + "Inference status: in-progress\n", + "{'inference': {'id': 'inf_dTXDbskJ57wm1EbdyZLLqHvC', 'userId': '8abf83b97f13c13ecb5090739c2a3461', 'ownerId': 'team_5XP3979oXCXmbtCbFpa6phBv', 'authorId': '8abf83b97f13c13ecb5090739c2a3461', 'modelId': 'WMFVfL6ASISizG1T7X2NNw', 'createdAt': '2024-04-01T22:22:44.083Z', 'parameters': {'modality': 'depth:0.9', 'qualityBoost': False, 'hideResults': False, 'type': 'controlnet', 'negativePrompt': 'ugly, bad, low quality, blurry', 'intermediateImages': False, 'guidance': 7.5, 'numInferenceSteps': 30, 'disableModalityDetection': False, 'numSamples': 2, 'tokenMerging': 0, 'width': 512, 'prompt': 'close up portrait of a sci-fi character in red armor with cyber helmet, lights on cyber mask, full armor, insulated armor, angry, active pose, strong warrior, weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting', 'height': 512, 'image': 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'https://cdn.cloud.scenario.com/assets-transform/asset_BxDSfjbqxZFwpiDFCMcC5N7a?p=100&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4uY2xvdWQuc2NlbmFyaW8uY29tL2Fzc2V0cy10cmFuc2Zvcm0vYXNzZXRfQnhEU2ZqYnF4WkZ3cGlERkNNY0M1TjdhP3A9MTAwKiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcxMzEzOTE5OX19fV19&Key-Pair-Id=K36FIAB9LE2OLR&Signature=WIs4QXXe2xU-Ecs4hD3enUeoyq2KZFNVhbVYIM0imY676Sj1vNMAWxLGJlLkB6qW9GJpEgrT1byrgEjldWH1~V48sUHzOuElw5OsGYtECVCVCZNLA3RgOXIx7~QgDBrCkPVyKfFjR8v49YNLkBzRIC0guaOt-JwkKX5kvk1S5f35lxcoN0vTfOJSSsnT2SR77SMv9hMCCjd6qWJ004LC2NooIdezA0ey0pCpnkjAP4rEeLTkJYQDuQOaJoh81lyqJII4yMbUyy9gIuSS07T6dJMg20weZvjyXeeSoinvxfb6H4egLuEW8nX~i3ce-12MnOkIIhgaaA3cZZoboe70UA__', 'seed': '10678558040096272450'}], 'imagesNumber': 2, 'progress': 1, 'displayPrompt': 'close up portrait of a sci-fi character in red armor with cyber helmet, lights on cyber mask, full armor, insulated armor, angry, active pose, strong warrior, weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting'}}\n", + "Inference status: succeeded\n", + "Inference succeeded!\n", + "{'inference': {'id': 'inf_dTXDbskJ57wm1EbdyZLLqHvC', 'userId': '8abf83b97f13c13ecb5090739c2a3461', 'ownerId': 'team_5XP3979oXCXmbtCbFpa6phBv', 'authorId': '8abf83b97f13c13ecb5090739c2a3461', 'modelId': 'WMFVfL6ASISizG1T7X2NNw', 'createdAt': '2024-04-01T22:22:44.083Z', 'parameters': {'modality': 'depth:0.9', 'qualityBoost': False, 'hideResults': False, 'type': 'controlnet', 'negativePrompt': 'ugly, bad, low quality, blurry', 'intermediateImages': False, 'guidance': 7.5, 'numInferenceSteps': 30, 'disableModalityDetection': False, 'numSamples': 2, 'tokenMerging': 0, 'width': 512, 'prompt': 'close up portrait of a sci-fi character in red armor with cyber helmet, lights on cyber mask, full armor, insulated armor, angry, active pose, strong warrior, weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting', 'height': 512, 'image': 'https://cdn.cloud.scenario.com/assets-transform/asset_Yg1SkWWXpSPb3CVYukDH6ixR?Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4uY2xvdWQuc2NlbmFyaW8uY29tL2Fzc2V0cy10cmFuc2Zvcm0vYXNzZXRfWWcxU2tXV1hwU1BiM0NWWXVrREg2aXhSKiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcxMzEzOTE5OX19fV19&Key-Pair-Id=K36FIAB9LE2OLR&Signature=AoJyccq~i~lrk~K4s87OQvCjY-CHNxBA44l-1ILpdg7cLpq8n7CoNunYS3Bf2BUAFLMW~zir1r147WhqdK9o5HhM7BOipWiqAgqvM9AMqPg70iLENYsgpkkUd9TwF75Nea8mt3iYFFNa6xm91dDI6dN42FhABCXh7wlE~gFhYXm2XNjN6S-3QJolsp76ejJJVXA0eyGSZpDZOZ5UwD0UmPy4CZzkbft7g9ONROZnkct59GmWqJAfbNWY9rqKNYHW6QSg7i6hG3LFbAgLRrKFSb4mQHGD54vz69L5sr8Sv7ol8HLEm3UCEvi4sSEP6NNadNNk6C1Ym~fZyBzXYXBewg__', 'imageId': 'asset_Yg1SkWWXpSPb3CVYukDH6ixR'}, 'status': 'succeeded', 'images': [{'id': 'asset_EHuZGfZNoNGX4Y4YozTwKEWY', 'url': 'https://cdn.cloud.scenario.com/assets-transform/asset_EHuZGfZNoNGX4Y4YozTwKEWY?p=100&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4uY2xvdWQuc2NlbmFyaW8uY29tL2Fzc2V0cy10cmFuc2Zvcm0vYXNzZXRfRUh1WkdmWk5vTkdYNFk0WW96VHdLRVdZP3A9MTAwKiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcxMzEzOTE5OX19fV19&Key-Pair-Id=K36FIAB9LE2OLR&Signature=KslsImSXPJyhjAFEdXAdTaHR3dfokI8VD44ei-~iYdN-xhYUX4e~hrjN84Wk6sKanyxOT0lFA5j4PGKRIoUGyd8iICJhf5NIkESB4fuuksvGRkXHDhZiNN-WvrKMImgWGgWkUQHsp60-9yA9D9ouV1dxnr69ftMUyYnMJ9NBRNxUWdjaEB~uygYDqV6wYbb6qWfUJD0iWl5UU9hm~e6meAp6uOhuSYxnTKUO09FeRlkcyuTymP3GaRM1vODJaEd-VEwpSo8CessSdyWKtzKQmtS5YCRtnbOwvCD3qq9nE7i0zGK1KnPiMfufxeEhGkg0IAQAlueGJb9cbRYWWV8nSg__', 'seed': '6655807731561520685'}, {'id': 'asset_BxDSfjbqxZFwpiDFCMcC5N7a', 'url': 'https://cdn.cloud.scenario.com/assets-transform/asset_BxDSfjbqxZFwpiDFCMcC5N7a?p=100&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4uY2xvdWQuc2NlbmFyaW8uY29tL2Fzc2V0cy10cmFuc2Zvcm0vYXNzZXRfQnhEU2ZqYnF4WkZ3cGlERkNNY0M1TjdhP3A9MTAwKiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcxMzEzOTE5OX19fV19&Key-Pair-Id=K36FIAB9LE2OLR&Signature=WIs4QXXe2xU-Ecs4hD3enUeoyq2KZFNVhbVYIM0imY676Sj1vNMAWxLGJlLkB6qW9GJpEgrT1byrgEjldWH1~V48sUHzOuElw5OsGYtECVCVCZNLA3RgOXIx7~QgDBrCkPVyKfFjR8v49YNLkBzRIC0guaOt-JwkKX5kvk1S5f35lxcoN0vTfOJSSsnT2SR77SMv9hMCCjd6qWJ004LC2NooIdezA0ey0pCpnkjAP4rEeLTkJYQDuQOaJoh81lyqJII4yMbUyy9gIuSS07T6dJMg20weZvjyXeeSoinvxfb6H4egLuEW8nX~i3ce-12MnOkIIhgaaA3cZZoboe70UA__', 'seed': '10678558040096272450'}], 'imagesNumber': 2, 'progress': 1, 'displayPrompt': 'close up portrait of a sci-fi character in red armor with cyber helmet, lights on cyber mask, full armor, insulated armor, angry, active pose, strong warrior, weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting'}}\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + } + ], + "source": [ + "\n", + "# Make a POST request to create an inference\n", + "\n", + "response = requests.post(f'{base_url}/models/{model_id}/inferences', json={\n", + " 'parameters': {\n", + " 'type': 'controlnet',\n", + " 'prompt':\n", + " 'close up portrait of a sci-fi character in red armor with cyber helmet, lights on cyber mask, full armor, insulated armor, angry, active pose, strong warrior, weapon, optimus prime style, bald head, lots of fine detail, sci-fi dark movie style, background: spaceship, photography, natural light, photorealism, cinematic rendering, ray tracing, highest quality, highest detail, Cinematic, Third-Person View, Blur Effect, Long Exposure, 8K, Ultra-HD, Moody Lighting, Cinematic Lighting',\n", + " 'image': base64_data_url, # Your image dataURL here\n", + " 'modality': 'depth:0.9', # Your modality and its scale, see API documentation\n", + " 'numInferenceSteps': 30,\n", + " 'numSamples': 2,\n", + " 'guidance': 7.5,\n", + " 'width': 512,\n", + " 'height': 512,\n", + " 'negativePrompt': 'ugly, bad, low quality, blurry',\n", + " }\n", + "}, headers=headers)\n", + "\n", + "\n", + "check_progress_get_results(response)\n" + ] + }, + { + "cell_type": "markdown", + "source": [ + "# IP Adapter + LCM Scheduler" + ], + "metadata": { + "id": "o2ssLFc4gFWc" + } + }, + { + "cell_type": "markdown", + "source": [ + "https://docs.scenario.com/recipes/ip-adapter-lcm\n", + "\n", + "LCM can be leveraged with the help of IP Adapters to maintain a consistent subject without sacrificing overall quality, beyond an acceptable threshold. In tests, outputs with LCM which previously only maintained 20-30% coherence as compared to the default scheduler, landed much closer to 70-80% consistency and fidelity.\n", + "\n", + "\n" + ], + "metadata": { + "id": "CBRPsSJUhdBY" + } + }, + { + "cell_type": "code", + "source": [ + "# Make a POST request to create an inference\n", + "response = requests.post(f\"{base_url}/models/{model_id}/inferences\", headers={\n", + " **headers,\n", + " 'Content-Type': 'application/json'\n", + "}, json={\n", + " 'parameters': {\n", + " 'type': 'txt2img',\n", + " 'prompt': 'portrait',\n", + " 'numInferenceSteps': 30,\n", + " 'numSamples': 2,\n", + " 'guidance': 7.5,\n", + " 'width': 1024,\n", + " 'height': 1024,\n", + " 'negativePrompt': 'ugly, bad, low quality, blurry',\n", + " }\n", + "})\n", + "\n", + "\n" + ], + "metadata": { + "id": "d7zbD6qSc19c" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "check_progress_set_lcm(response, 'purple hair')" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "mZpJCRIagIvn", + "outputId": "631e38c2-99fb-4424-f0e0-dd658e31354e" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "{'inference': {'id': 'inf_5BrwW8egdeCmdHDPFdKoJAdm', 'userId': '8abf83b97f13c13ecb5090739c2a3461', 'ownerId': 'team_5XP3979oXCXmbtCbFpa6phBv', 'authorId': '8abf83b97f13c13ecb5090739c2a3461', 'modelId': 'WMFVfL6ASISizG1T7X2NNw', 'createdAt': '2024-03-31T21:53:08.708Z', 'parameters': {'type': 'txt2img', 'prompt': 'portrait', 'negativePrompt': 'ugly, bad, low quality, blurry', 'numSamples': 2, 'intermediateImages': False, 'guidance': 7.5, 'numInferenceSteps': 30, 'width': 1024, 'height': 1024, 'hideResults': False, 'tokenMerging': 0, 'qualityBoost': False}, 'status': 'queued', 'images': [], 'imagesNumber': 0, 'displayPrompt': 'portrait'}, 'creativeUnitsCost': 32}\n", + "{'inference': {'id': 'inf_5BrwW8egdeCmdHDPFdKoJAdm', 'userId': '8abf83b97f13c13ecb5090739c2a3461', 'ownerId': 'team_5XP3979oXCXmbtCbFpa6phBv', 'authorId': '8abf83b97f13c13ecb5090739c2a3461', 'modelId': 'WMFVfL6ASISizG1T7X2NNw', 'createdAt': '2024-03-31T21:53:08.708Z', 'parameters': {'intermediateImages': False, 'guidance': 7.5, 'numInferenceSteps': 30, 'qualityBoost': False, 'numSamples': 2, 'tokenMerging': 0, 'width': 1024, 'hideResults': False, 'type': 'txt2img', 'prompt': 'portrait', 'negativePrompt': 'ugly, bad, low quality, blurry', 'height': 1024}, 'status': 'succeeded', 'images': [{'id': 'asset_Ykdw2ZZaNvb4KZRfik1yzxB9', 'url': 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'https://cdn.cloud.scenario.com/assets-transform/asset_R6Az43GDnsQxZq61zKh1236t?p=100&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4uY2xvdWQuc2NlbmFyaW8uY29tL2Fzc2V0cy10cmFuc2Zvcm0vYXNzZXRfUjZBejQzR0Ruc1F4WnE2MXpLaDEyMzZ0P3A9MTAwKiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcxMjUzNDM5OX19fV19&Key-Pair-Id=K36FIAB9LE2OLR&Signature=Dsr4tac3~3M58Yt4zKzeKb8~qVqeijbjlaYg8SawqZpO1pWnLdSCltZBRtgXhkdF1i-v6rpK~ceNJEP-boyPRI9g~GC7gxEc9~pd6wZQngFqUE5UbwQHv23Gf0o1lcsWZgolU4Ahj7Ln10XCH0Xa3miMnbZcvjGcjgz2OsVr86DSJmIHs-OmEvxNbxQB-Z3NEgLmj7eGHVryLnctfj8yKKiNNevMcJ80PTp~l5CdT6~T4mzKcWsCBsrGWJTjqNEIo3yMsgz5aujqz7kQI3V0uEkJ5r7aeGFcbgnGSl2x~sdnV1-gOEc~xxLYwcpPbdomt5C1mPdUz1ozy6wnGYI3wQ__', 'seed': '2664900869426147614'}], 'imagesNumber': 2, 'progress': 1, 'displayPrompt': 'portrait'}}\n", + "Inference status: succeeded\n", + "Inference succeeded!\n", + "{'inference': {'id': 'inf_5BrwW8egdeCmdHDPFdKoJAdm', 'userId': '8abf83b97f13c13ecb5090739c2a3461', 'ownerId': 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