local run

localAPIRun.py

@@ -0,0 +1,163 @@
+from datetime import datetime
+import urllib.request
+import base64
+import json
+import time
+import os
+url="pop-os.local"
+webui_server_url = f'http://{url}:7860'
+
+out_dir = 'api_out'
+out_dir_t2i = os.path.join(out_dir, 'txt2img')
+out_dir_i2i = os.path.join(out_dir, 'img2img')
+os.makedirs(out_dir_t2i, exist_ok=True)
+os.makedirs(out_dir_i2i, exist_ok=True)
+
+
+def timestamp():
+    return datetime.fromtimestamp(time.time()).strftime("%Y%m%d-%H%M%S")
+
+
+def encode_file_to_base64(path):
+    with open(path, 'rb') as file:
+        return base64.b64encode(file.read()).decode('utf-8')
+
+
+def decode_and_save_base64(base64_str, save_path):
+    with open(save_path, "wb") as file:
+        file.write(base64.b64decode(base64_str))
+
+
+def call_api(api_endpoint, **payload):
+    data = json.dumps(payload).encode('utf-8')
+    request = urllib.request.Request(
+        f'{webui_server_url}/{api_endpoint}',
+        headers={'Content-Type': 'application/json'},
+        data=data,
+    )
+    response = urllib.request.urlopen(request)
+    return json.loads(response.read().decode('utf-8'))
+
+
+def call_txt2img_api(**payload):
+    response = call_api('sdapi/v1/txt2img', **payload)
+    for index, image in enumerate(response.get('images')):
+        save_path = os.path.join(out_dir_t2i, f'txt2img-{timestamp()}-{index}.png')
+        decode_and_save_base64(image, save_path)
+
+
+def call_img2img_api(**payload):
+    response = call_api('sdapi/v1/img2img', **payload)
+    for index, image in enumerate(response.get('images')):
+        save_path = os.path.join(out_dir_i2i, f'img2img-{timestamp()}-{index}.png')
+        decode_and_save_base64(image, save_path)
+
+
+if __name__ == '__main__':
+    payload = {
+        "prompt": "masterpiece, (best quality:1.1), 1girl <lora:lora_model:1>",  # extra networks also in prompts
+        "negative_prompt": "",
+        "seed": 1,
+        "steps": 20,
+        "width": 512,
+        "height": 512,
+        "cfg_scale": 7,
+        "sampler_name": "DPM++ 2M",
+        "n_iter": 1,
+        "batch_size": 1,
+
+        # example args for x/y/z plot
+        # "script_name": "x/y/z plot",
+        # "script_args": [
+        #     1,
+        #     "10,20",
+        #     [],
+        #     0,
+        #     "",
+        #     [],
+        #     0,
+        #     "",
+        #     [],
+        #     True,
+        #     True,
+        #     False,
+        #     False,
+        #     0,
+        #     False
+        # ],
+
+        # example args for Refiner and ControlNet
+        # "alwayson_scripts": {
+        #     "ControlNet": {
+        #         "args": [
+        #             {
+        #                 "batch_images": "",
+        #                 "control_mode": "Balanced",
+        #                 "enabled": True,
+        #                 "guidance_end": 1,
+        #                 "guidance_start": 0,
+        #                 "image": {
+        #                     "image": encode_file_to_base64(r"B:\path\to\control\img.png"),
+        #                     "mask": None  # base64, None when not need
+        #                 },
+        #                 "input_mode": "simple",
+        #                 "is_ui": True,
+        #                 "loopback": False,
+        #                 "low_vram": False,
+        #                 "model": "control_v11p_sd15_canny [d14c016b]",
+        #                 "module": "canny",
+        #                 "output_dir": "",
+        #                 "pixel_perfect": False,
+        #                 "processor_res": 512,
+        #                 "resize_mode": "Crop and Resize",
+        #                 "threshold_a": 100,
+        #                 "threshold_b": 200,
+        #                 "weight": 1
+        #             }
+        #         ]
+        #     },
+        #     "Refiner": {
+        #         "args": [
+        #             True,
+        #             "sd_xl_refiner_1.0",
+        #             0.5
+        #         ]
+        #     }
+        # },
+        # "enable_hr": True,
+        # "hr_upscaler": "R-ESRGAN 4x+ Anime6B",
+        # "hr_scale": 2,
+        # "denoising_strength": 0.5,
+        # "styles": ['style 1', 'style 2'],
+        # "override_settings": {
+        #     'sd_model_checkpoint': "sd_xl_base_1.0",  # this can use to switch sd model
+        # },
+    }
+    call_txt2img_api(**payload)
+
+    init_images = [
+        encode_file_to_base64(r"../stable-diffusion-webui/output/img2img-images/2024-05-15/00012-357584826.png"),
+        # encode_file_to_base64(r"B:\path\to\img_2.png"),
+        # "https://image.can/also/be/a/http/url.png",
+    ]
+
+    batch_size = 2
+    payload = {
+        "prompt": "1girl, blue hair",
+        "seed": 1,
+        "steps": 20,
+        "width": 512,
+        "height": 512,
+        "denoising_strength": 0.5,
+        "n_iter": 1,
+        "init_images": init_images,
+        "batch_size": batch_size if len(init_images) == 1 else len(init_images),
+        # "mask": encode_file_to_base64(r"B:\path\to\mask.png")
+    }
+    # if len(init_images) > 1 then batch_size should be == len(init_images)
+    # else if len(init_images) == 1 then batch_size can be any value int >= 1
+    call_img2img_api(**payload)
+
+    # there exist a useful extension that allows converting of webui calls to api payload
+    # particularly useful when you wish setup arguments of extensions and scripts
+    # https://github.com/huchenlei/sd-webui-api-payload-display