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import requests |
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import cv2 |
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import numpy as np |
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from base64 import b64encode , b64decode |
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from PIL import Image |
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import io |
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def readImage(path): |
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img = cv2.imread(path) |
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retval, buffer = cv2.imencode('.jpg', img) |
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b64img = b64encode(buffer).decode("utf-8") |
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return b64img |
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def readb64(uri): |
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nparr = np.fromstring(b64decode(uri), np.uint8) |
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img = cv2.imdecode(nparr, cv2.IMREAD_COLOR) |
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return img |
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b64img = readImage("output_image.png") |
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class controlnetRequest(): |
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def __init__(self, prompt): |
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self.url = "http://127.0.0.1:7860/controlnet/txt2img" |
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self.body = { |
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"prompt": prompt, |
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"negative_prompt": "", |
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"seed": -1, |
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"subseed": -1, |
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"subseed_strength": 0, |
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"batch_size": 1, |
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"n_iter": 1, |
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"steps": 30, |
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"cfg_scale": 14, |
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"width": 512, |
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"height": 512, |
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"restore_faces": True, |
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"eta": 0, |
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"sampler_index": "DDIM", |
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"controlnet_model": "Test_ziva", |
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"controlnet_input_image": [b64img], |
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"controlnet_module": 'depth', |
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"ControlNet Weight": 1, |
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"controlnet_model": 'control_sd15_depth [fef5e48e]', |
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"controlnet_guidance": 1 |
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} |
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def sendRequest(self): |
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r = requests.post(self.url, json=self.body) |
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print(r) |
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return r.json() |
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js = controlnetRequest("clothed busty bird").sendRequest() |
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for x,i in enumerate(js['images']): |
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image = Image.open(io.BytesIO(b64decode(i.split(",",1)[0]))) |
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image.save(str(x)+'output.png') |
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len(js['images']) |
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print(js) |
