'commit'

BaiHu/Test/TestImg2Img.py

@@ -1,39 +1,11 @@
-import base64
-import json
-
-
-def encode_image(image_path):
-    with open(image_path, "rb") as i:
-        b64 = base64.b64encode(i.read())
-    return b64.decode("utf-8")
-
-
-# 读取JSON文件
-json_file = r'../JSON/28_1.json'
-with open(json_file, 'r', encoding='utf-8') as file:
-    payload = json.load(file)
-
-# 此处为读取一张图片作为输入图像
-refer_img = encode_image('../Image/28/1.jpg')
-source_img = encode_image('../Image/1ae93e2587822c291362abf9504cb49ec.jpeg')
-
-payload["alwayson_scripts"]["ControlNet"]["args"][0]["input_image"] = source_img  # 按用户输入的图片进行面部参考
-payload["init_images"] = [refer_img]  # 图生图，风格参考图是输入
-payload["alwayson_scripts"]["ControlNet"]["args"][1]["input_image"] = refer_img
-print(json.dumps(payload, sort_keys=False, ensure_ascii=False, indent=4))  # 生成可以正确显示中文的json格式输出
+from Util.CommonUtil import *
 
 # API地址
 url = "http://192.168.1.21:7860"
-# response = requests.post(url=f'{url}/sdapi/v1/img2img', json=payload)
-
-# if response.status_code != 200:
-#    print(response.text)
-#    exit(0)
-# r = response.json()
-
-# image = Image.open(io.BytesIO(base64.b64decode(r['images'][0])))
-
+# 用户输入的源图
+input_source_img = '../Image/1ae93e2587822c291362abf9504cb49ec.jpeg'
+# 输出图片
+output_file = "../Out/Result.png"
 
-# print(payload)
-# image.show()
-# image.save('output.png')
+# 调用图生图
+img2img(url, 28, 1, input_source_img, output_file)

BaiHu/Util/CommonUtil.py

@@ -103,3 +103,34 @@ def split_4_image(image_path, out_path):
     bottom_right.save(fi)
 
     return res
+
+
+# 图生图函数
+def img2img(url,model_id, prompt_id, input_source_img, output_file):
+    # JSON文件模板
+    templet_file = r'../JSON/' + str(model_id) + '_' + str(prompt_id) + '.json'
+    # 模型图片
+    input_refer_img = '../Image/' + str(model_id) + '/' + str(prompt_id) + '.jpg'
+
+    # 读取JSON文件
+    with open(templet_file, 'r', encoding='utf-8') as file:
+        payload = json.load(file)
+
+    # 用户输入的图片
+    source_img = encode_image(input_source_img)
+    # 模型固定的参考图片
+    refer_img = encode_image(input_refer_img)
+
+    # 在ControlNet的第一个图片中使用用户输入的图片，用此图片的人脸进行换脸操作
+    payload["alwayson_scripts"]["ControlNet"]["args"][0]["input_image"] = source_img
+    # 图生图，风格参考图是输入
+    payload["init_images"] = [refer_img]
+    payload["alwayson_scripts"]["ControlNet"]["args"][1]["input_image"] = refer_img
+    # 调用SD服务
+    response = requests.post(url=f'{url}/sdapi/v1/img2img', json=payload)
+    if response.status_code != 200:
+        print(response.text)
+        exit(0)
+    r = response.json()
+    # 保存图片
+    save_encoded_image(response.json()['images'][0], output_file)