Update clothGen.py

clothGen.py

@@ -1,77 +1,77 @@
-import fal_client
-import pandas as pd
-from prompt_gen import prompt_gen
-import requests
-import os
-
-nv_prompt_file = pd.read_excel('汉服-女词库.xlsx')
-na_prompt_file = pd.read_excel('汉服-男词库.xlsx')
-nv_prompt = nv_prompt_file.to_string(index=False)
-na_prompt = na_prompt_file.to_string(index=False)
-
-
-def cloth_gen(advice, gender):
-    lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors"
-    if gender == "男":
-        lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NA.safetensors"
-    else:
-        lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors"
-
-    prompt = prompt_gen(advice, gender)
-    start_index = prompt.find("prompt" or "Prompt")
-    intro_index = prompt.find("服饰风格介绍")
-    cloth_intro = ""
-    promptGen = ""
-    if start_index != -1:
-        start_index += len("prompt\n\n")
-        end_index = prompt.find("promptEnd")
-        if end_index != -1:
-            extracted_content = prompt[start_index:end_index]
-            promptGen = extracted_content
-            print(extracted_content)
-        else:
-            print("No 'promptEnd' found after 'prompt'.")
-    else:
-        print("No 'prompt' found in the text.")
-    if intro_index != -1:
-        intro_index += len("服饰风格介绍\n\n")
-        cloth_intro = ("汉服，是汉民族的传统服饰。又称衣冠、衣裳、汉装。汉服是中国“衣冠上国”“礼仪之邦”“锦绣中华”的体现，承载了中国的染织绣等杰出"
-                       "工艺和美学，传承了30多项中国非物质文化遗产以及受保护的中国工艺美术。\n") + prompt[intro_index:]
-        print(cloth_intro)
-    else:
-        print("No '服饰风格介绍' found.")
-
-    handler = fal_client.submit(
-        "fal-ai/fast-sdxl",
-        arguments={
-            "prompt": promptGen,
-            "negative_prompt": "human, people, person, man, woman, child, model, face, head, eyes, hands, arms, legs, "
-                               "feet, hair, portrait, worst quality, low quality, normal quality, lowres, signature, "
-                               "watermark, jpeg artifacts, logo, monochrome, grayscale, ugly",
-            "image_size": "portrait_4_3",
-            "num_inference_steps": 28,
-            "guidance_scale": 7.5,
-            "num_images": 6,
-            "loras": [{"path": lora_path, "scale": 0.7}],
-            "embeddings": [],
-            "safety_checker_version": "v1",
-            "format": "jpeg"
-        },
-    )
-
-    request_id = handler.request_id
-    result = fal_client.result("fal-ai/fast-sdxl", request_id)
-    cloth_image = []
-    save_directory = "downloads"
-    image_index = 1
-    for image in result['images']:
-        response = requests.get(image['url'])
-        if response.status_code == 200:
-            filename = os.path.join(save_directory, f"gen_cloth_{image_index}.jpeg")
-            cloth_image.append(filename)
-            with open(filename, 'wb') as f:
-                f.write(response.content)
-            image_index += 1
-        else:
-            print(f"Failed to download image from {image['url']}")
-    return cloth_image, cloth_image[0], cloth_intro
+import fal_client
+import pandas as pd
+from prompt_gen import prompt_gen
+import requests
+import os
+
+nv_prompt_file = pd.read_excel('汉服-女词库.xlsx')
+na_prompt_file = pd.read_excel('汉服-男词库.xlsx')
+nv_prompt = nv_prompt_file.to_string(index=False)
+na_prompt = na_prompt_file.to_string(index=False)
+
+
+def cloth_gen(advice, gender):
+    lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors"
+    if gender == "男":
+        lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NA.safetensors"
+    else:
+        lora_path = "https://huggingface.co/PPSharks/PPSharksModels/resolve/main/NV.safetensors"
+
+    prompt = prompt_gen(advice, gender)
+    start_index = prompt.find("prompt" or "Prompt")
+    intro_index = prompt.find("服饰风格介绍")
+    cloth_intro = ""
+    promptGen = ""
+    if start_index != -1:
+        start_index += len("prompt\n\n")
+        end_index = prompt.find("promptEnd")
+        if end_index != -1:
+            extracted_content = prompt[start_index:end_index]
+            promptGen = extracted_content
+            print(extracted_content)
+        else:
+            print("No 'promptEnd' found after 'prompt'.")
+    else:
+        print("No 'prompt' found in the text.")
+    if intro_index != -1:
+        intro_index += len("服饰风格介绍\n")
+        cloth_intro = ("汉服，是汉民族的传统服饰。又称衣冠、衣裳、汉装。汉服是中国“衣冠上国”“礼仪之邦”“锦绣中华”的体现，承载了中国的染织绣等杰出"
+                       "工艺和美学，传承了30多项中国非物质文化遗产以及受保护的中国工艺美术。\n") + prompt[intro_index:]
+        print(cloth_intro)
+    else:
+        print("No '服饰风格介绍' found.")
+
+    handler = fal_client.submit(
+        "fal-ai/fast-sdxl",
+        arguments={
+            "prompt": promptGen,
+            "negative_prompt": "human, people, person, man, woman, child, model, face, head, eyes, hands, arms, legs, "
+                               "feet, hair, portrait, worst quality, low quality, normal quality, lowres, signature, "
+                               "watermark, jpeg artifacts, logo, monochrome, grayscale, ugly",
+            "image_size": "portrait_4_3",
+            "num_inference_steps": 28,
+            "guidance_scale": 7.5,
+            "num_images": 6,
+            "loras": [{"path": lora_path, "scale": 0.7}],
+            "embeddings": [],
+            "safety_checker_version": "v1",
+            "format": "jpeg"
+        },
+    )
+
+    request_id = handler.request_id
+    result = fal_client.result("fal-ai/fast-sdxl", request_id)
+    cloth_image = []
+    save_directory = "downloads"
+    image_index = 1
+    for image in result['images']:
+        response = requests.get(image['url'])
+        if response.status_code == 200:
+            filename = os.path.join(save_directory, f"gen_cloth_{image_index}.jpeg")
+            cloth_image.append(filename)
+            with open(filename, 'wb') as f:
+                f.write(response.content)
+            image_index += 1
+        else:
+            print(f"Failed to download image from {image['url']}")
+    return cloth_image, cloth_image[0], cloth_intro