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feifeilib/feifeichat.py

@@ -45,23 +45,26 @@ def feifeichat(message, history, feifei_select):
         # Specify model
         model = "pixtral-large-2411"
         # Define the messages for the chat
-        messages = [
-            {
-                "role": "user",
-                "content": [
-                    {"type": "text", "text": message_text},
-                    {
-                        "type": "image_url",
-                        "image_url": f"data:image/jpeg;base64,{base64_image}",
-                    },
-                ],
-            }
-        ]
+        messages = [{
+            "role":
+            "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": message_text
+                },
+                {
+                    "type": "image_url",
+                    "image_url": f"data:image/jpeg;base64,{base64_image}",
+                },
+            ],
+        }]
 
         partial_message = ""
         for chunk in client.chat.stream(model=model, messages=messages):
             if chunk.data.choices[0].delta.content is not None:
-                partial_message = partial_message + chunk.data.choices[0].delta.content
+                partial_message = partial_message + chunk.data.choices[
+                    0].delta.content
                 yield partial_message
 
     else:
@@ -76,7 +79,8 @@ def feifeichat(message, history, feifei_select):
 
             if history:
                 history = [
-                    item for item in history if not pattern.search(str(item["content"]))
+                    item for item in history
+                    if not pattern.search(str(item["content"]))
                 ]
                 # print(history)
                 input_prompt = [system_prompt] + history + [user_input_part]
@@ -84,10 +88,12 @@ def feifeichat(message, history, feifei_select):
                 input_prompt = [system_prompt] + [user_input_part]
         else:
             input_prompt = [{"role": "user", "content": str(message)}]
-        stream_response = client.chat.stream(model=model, messages=input_prompt)
+        stream_response = client.chat.stream(model=model,
+                                             messages=input_prompt)
 
         partial_message = ""
         for chunk in stream_response:
             if chunk.data.choices[0].delta.content is not None:
-                partial_message = partial_message + chunk.data.choices[0].delta.content
+                partial_message = partial_message + chunk.data.choices[
+                    0].delta.content
                 yield partial_message

feifeilib/feifeiflorence.py

@@ -18,18 +18,18 @@ device = "cuda:0" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 
 Florence_models = AutoModelForCausalLM.from_pretrained(
-    "microsoft/Florence-2-large", torch_dtype=torch_dtype, trust_remote_code=True
-).to(device)
+    "microsoft/Florence-2-large",
+    torch_dtype=torch_dtype,
+    trust_remote_code=True).to(device)
 
 Florence_processors = AutoProcessor.from_pretrained(
-    "microsoft/Florence-2-large", trust_remote_code=True
-)
+    "microsoft/Florence-2-large", trust_remote_code=True)
 
 
 @spaces.GPU
 def feifeiflorence(
-    image,
-    progress=gr.Progress(track_tqdm=True),
+        image,
+        progress=gr.Progress(track_tqdm=True),
 ):
     image = Image.fromarray(image)
     task_prompt = "<MORE_DETAILED_CAPTION>"
@@ -37,9 +37,9 @@ def feifeiflorence(
     if image.mode != "RGB":
         image = image.convert("RGB")
 
-    inputs = Florence_processors(
-        text=task_prompt, images=image, return_tensors="pt"
-    ).to(device, torch_dtype)
+    inputs = Florence_processors(text=task_prompt,
+                                 images=image,
+                                 return_tensors="pt").to(device, torch_dtype)
 
     generated_ids = Florence_models.generate(
         input_ids=inputs["input_ids"],
@@ -49,9 +49,9 @@ def feifeiflorence(
         do_sample=False,
     )
     generated_text = Florence_processors.batch_decode(
-        generated_ids, skip_special_tokens=False
-    )[0]
+        generated_ids, skip_special_tokens=False)[0]
     parsed_answer = Florence_processors.post_process_generation(
-        generated_text, task=task_prompt, image_size=(image.width, image.height)
-    )
+        generated_text,
+        task=task_prompt,
+        image_size=(image.width, image.height))
     return parsed_answer["<MORE_DETAILED_CAPTION>"]

feifeilib/feifeiimgtoimg.py

@@ -4,5 +4,6 @@ import numpy as np
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 4096
 
+
 def feifeiimgtoimg(img_in_result, prompt):
     return img_in_result

feifeilib/feifeitexttoimg.py

@@ -23,19 +23,19 @@ artists = [artist.strip() for artist in artists]
 
 @spaces.GPU()
 def feifeitexttoimg(
-    prompt,
-    quality_select,
-    sharpened_select,
-    styles_Radio,
-    FooocusExpansion_select,
-    seed=42,
-    randomize_seed=False,
-    width=1024,
-    height=1024,
-    num_inference_steps=4,
-    guidance_scale=3.5,
-    num_strength=0.35,
-    progress=gr.Progress(track_tqdm=True),
+        prompt,
+        quality_select,
+        sharpened_select,
+        styles_Radio,
+        FooocusExpansion_select,
+        seed=42,
+        randomize_seed=False,
+        width=1024,
+        height=1024,
+        num_inference_steps=4,
+        guidance_scale=3.5,
+        num_strength=0.35,
+        progress=gr.Progress(track_tqdm=True),
 ):
     guidance_scale = 3.5
     if randomize_seed:
@@ -85,41 +85,37 @@ def feifeitexttoimg(
         image_np = np.array(image)
 
         # 将NumPy数组转换为PyTorch张量
-        image_tensor = (
-            torch.tensor(image_np).permute(2, 0, 1).unsqueeze(0).float().to("cuda")
-        )
+        image_tensor = (torch.tensor(image_np).permute(
+            2, 0, 1).unsqueeze(0).float().to("cuda"))
 
         # 定义锐化滤镜，并调整中心值
         strength = num_strength
-        sharpen_kernel = (
-            torch.tensor(
-                [
-                    [0, -1 * strength, 0],
-                    [-1 * strength, 1 + 4 * strength, -1 * strength],
-                    [0, -1 * strength, 0],
-                ],
-                dtype=torch.float32,
-            )
-            .unsqueeze(0)
-            .unsqueeze(0)
-            .to("cuda")
-        )
+        sharpen_kernel = (torch.tensor(
+            [
+                [0, -1 * strength, 0],
+                [-1 * strength, 1 + 4 * strength, -1 * strength],
+                [0, -1 * strength, 0],
+            ],
+            dtype=torch.float32,
+        ).unsqueeze(0).unsqueeze(0).to("cuda"))
 
         # 分别对每个通道应用卷积核
         sharpened_channels = []
         for i in range(3):
-            channel_tensor = image_tensor[:, i : i + 1, :, :]
-            sharpened_channel = F.conv2d(channel_tensor, sharpen_kernel, padding=1)
+            channel_tensor = image_tensor[:, i:i + 1, :, :]
+            sharpened_channel = F.conv2d(channel_tensor,
+                                         sharpen_kernel,
+                                         padding=1)
             sharpened_channels.append(sharpened_channel)
 
         # 合并通道
         sharpened_image_tensor = torch.cat(sharpened_channels, dim=1)
 
         # 将增强后的图像转换回PIL格式
-        sharpened_image_np = (
-            sharpened_image_tensor.squeeze(0).permute(1, 2, 0).cpu().numpy()
-        )
-        sharpened_image_np = np.clip(sharpened_image_np, 0, 255).astype(np.uint8)
+        sharpened_image_np = (sharpened_image_tensor.squeeze(0).permute(
+            1, 2, 0).cpu().numpy())
+        sharpened_image_np = np.clip(sharpened_image_np, 0,
+                                     255).astype(np.uint8)
         image = Image.fromarray(sharpened_image_np)
 
     return image, seed

feifeiui/feifeiui.py

@@ -31,12 +31,11 @@ def create_ui():
                         container=False,
                     )
                     run_button = gr.Button("Run")
-                    result = gr.Image(
-                        label="Result", show_label=False, interactive=False
-                    )
+                    result = gr.Image(label="Result",
+                                      show_label=False,
+                                      interactive=False)
 
                     with gr.Accordion("Advanced Settings", open=False):
-
                         seed = gr.Slider(
                             label="Seed",
                             minimum=0,
@@ -45,10 +44,10 @@ def create_ui():
                             value=0,
                         )
 
-                        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+                        randomize_seed = gr.Checkbox(label="Randomize seed",
+                                                     value=True)
 
                         with gr.Row():
-
                             width = gr.Slider(
                                 label="Width",
                                 minimum=256,
@@ -97,23 +96,26 @@ def create_ui():
                         container=False,
                     )
                     img_run_button = gr.Button("Img2Img")
-                    img_out_result = gr.Image(
-                        label="Result", show_label=False, interactive=False
-                    )
+                    img_out_result = gr.Image(label="Result",
+                                              show_label=False,
+                                              interactive=False)
                 with gr.Tab("Styles"):
                     quality_select = gr.Checkbox(label="high quality")
-                    sharpened_select = gr.Checkbox(label="Sharpened")
+                    sharpened_select = gr.Checkbox(label="Sharpened",
+                                                   value=True)
                     FooocusExpansion_select = gr.Checkbox(
-                        label="FooocusExpansion", value=True
-                    )
-                    styles_name = [style["name"] for style in config.style_list]
-                    styles_Radio = gr.Dropdown(
-                        styles_name, label="Styles", multiselect=True
-                    )
+                        label="FooocusExpansion", value=True)
+                    styles_name = [
+                        style["name"] for style in config.style_list
+                    ]
+                    styles_Radio = gr.Dropdown(styles_name,
+                                               label="Styles",
+                                               multiselect=True)
                 with gr.Tab("Florence-2"):
                     with gr.Row():
                         with gr.Column():
-                            output_text = gr.Textbox(label="Output Text", container=False)
+                            output_text = gr.Textbox(label="Output Text",
+                                                     container=False)
                             florence_btn = gr.Button(value="Florence")
                         with gr.Column():
                             input_img = gr.Image(label="Input Picture")