Merge pull request #248 from mrhan1993/dev

Support image custom format

fooocusapi/api_utils.py

@@ -167,6 +167,7 @@ def req_to_params(req: Text2ImgRequest) -> ImageGenerationParams:
                                  inpaint_additional_prompt=inpaint_additional_prompt,
                                  image_prompts=image_prompts,
                                  advanced_params=advanced_params,
+                                 save_extension=req.save_extension,
                                  require_base64=req.require_base64,
                                  )
 

fooocusapi/file_utils.py

@@ -5,6 +5,11 @@
 import numpy as np
 from PIL import Image
 import uuid
+import json
+from pathlib import Path
+from PIL.PngImagePlugin import PngInfo
+
+
 
 output_dir = os.path.abspath(os.path.join(
     os.path.dirname(__file__), '..', 'outputs', 'files'))
@@ -13,16 +18,41 @@
 static_serve_base_url = 'http://127.0.0.1:8888/files/'
 
 
-def save_output_file(img: np.ndarray) -> str:
+def save_output_file(img: np.ndarray, image_meta: dict = None,
+                     image_name: str = '', extension: str = 'png') -> str:
+    """
+    Save np image to file
+    Args:
+        img: np.ndarray image to save
+        image_meta: dict of image metadata
+        image_name: str of image name
+        extension: str of image extension
+    Returns:
+        str of file name
+    """
     current_time = datetime.datetime.now()
     date_string = current_time.strftime("%Y-%m-%d")
 
-    filename = os.path.join(date_string, str(uuid.uuid4()) + '.png')
+    image_name = str(uuid.uuid4()) if image_name == '' else image_name
+
+    filename = os.path.join(date_string, image_name + '.' + extension)
     file_path = os.path.join(output_dir, filename)
 
+    if extension not in ['png', 'jpg', 'webp']:
+        extension = 'png'
+
+    if image_meta is None:
+        image_meta = {}
+
+    meta = None
+    if extension == 'png':
+        meta = PngInfo()
+        meta.add_text("params", json.dumps(image_meta))
+
     os.makedirs(os.path.dirname(file_path), exist_ok=True)
-    Image.fromarray(img).save(file_path)
-    return filename
+    Image.fromarray(img).save(file_path, format=extension,
+                              pnginfo=meta, optimize=True)
+    return Path(filename).as_posix()
 
 
 def delete_output_file(filename: str):

fooocusapi/models.py

@@ -123,6 +123,7 @@ class Text2ImgRequest(BaseModel):
     refiner_switch: float = Field(default=default_refiner_switch, description="Refiner Switch At", ge=0.1, le=1.0)
     loras: List[Lora] = Field(default=default_loras_model)
     advanced_params: AdvancedParams | None = AdvancedParams()
+    save_extension: str = Field(default='png', description="Save extension, one of [png, jpg, webp]")
     require_base64: bool = Field(default=False, description="Return base64 data of generated image")
     async_process: bool = Field(default=False, description="Set to true will run async and return job info for retrieve generataion result later")
     webhook_url: str | None = Field(default='', description="Optional URL for a webhook callback. If provided, the system will send a POST request to this URL upon task completion or failure."
@@ -214,6 +215,7 @@ def as_form(cls, input_image: UploadFile = Form(description="Init image for upsa
                 refiner_switch: float = Form(default=default_refiner_switch, description="Refiner Switch At", ge=0.1, le=1.0),
                 loras: str | None = Form(default=default_loras_json, description='Lora config in JSON. Format as [{"model_name": "sd_xl_offset_example-lora_1.0.safetensors", "weight": 0.5}]'),
                 advanced_params: str | None = Form(default=None, description="Advanced parameters in JSON"),
+                save_extension: str = Form(default="png", description="Save extension, png, jpg or webp"),
                 require_base64: bool = Form(default=False, description="Return base64 data of generated image"),
                 async_process: bool = Form(default=False, description="Set to true will run async and return job info for retrieve generataion result later"),
                 ):
@@ -226,7 +228,8 @@ def as_form(cls, input_image: UploadFile = Form(description="Init image for upsa
                    performance_selection=performance_selection, aspect_ratios_selection=aspect_ratios_selection,
                    image_number=image_number, image_seed=image_seed, sharpness=sharpness, guidance_scale=guidance_scale,
                    base_model_name=base_model_name, refiner_model_name=refiner_model_name, refiner_switch=refiner_switch,
-                   loras=loras_model, advanced_params=advanced_params_obj, require_base64=require_base64, async_process=async_process)
+                   loras=loras_model, advanced_params=advanced_params_obj, save_extension=save_extension,
+                   require_base64=require_base64, async_process=async_process)
 
 
 class ImgInpaintOrOutpaintRequest(Text2ImgRequest):
@@ -262,6 +265,7 @@ def as_form(cls, input_image: UploadFile = Form(description="Init image for inpa
                 refiner_switch: float = Form(default=default_refiner_switch, description="Refiner Switch At", ge=0.1, le=1.0),
                 loras: str | None = Form(default=default_loras_json, description='Lora config in JSON. Format as [{"model_name": "sd_xl_offset_example-lora_1.0.safetensors", "weight": 0.5}]'),
                 advanced_params: str| None = Form(default=None, description="Advanced parameters in JSON"),
+                save_extension: str = Form(default="png", description="Save extension, png, jpg or webp"),
                 require_base64: bool = Form(default=False, description="Return base64 data of generated image"),
                 async_process: bool = Form(default=False, description="Set to true will run async and return job info for retrieve generataion result later"),
                 ):
@@ -281,7 +285,7 @@ def as_form(cls, input_image: UploadFile = Form(description="Init image for inpa
                    performance_selection=performance_selection, aspect_ratios_selection=aspect_ratios_selection,
                    image_number=image_number, image_seed=image_seed, sharpness=sharpness, guidance_scale=guidance_scale,
                    base_model_name=base_model_name, refiner_model_name=refiner_model_name, refiner_switch=refiner_switch,
-                   loras=loras_model, advanced_params=advanced_params_obj, require_base64=require_base64, async_process=async_process)
+                   loras=loras_model, advanced_params=advanced_params_obj, save_extension=save_extension, require_base64=require_base64, async_process=async_process)
 
 
 class ImgPromptRequest(ImgInpaintOrOutpaintRequest):
@@ -343,6 +347,7 @@ def as_form(cls, input_image: UploadFile = Form(File(None), description="Init im
                 refiner_switch: float = Form(default=default_refiner_switch, description="Refiner Switch At", ge=0.1, le=1.0),
                 loras: str | None = Form(default=default_loras_json, description='Lora config in JSON. Format as [{"model_name": "sd_xl_offset_example-lora_1.0.safetensors", "weight": 0.5}]'),
                 advanced_params: str| None = Form(default=None, description="Advanced parameters in JSON"),
+                save_extension: str = Form(default="png", description="Save extension, png, jpg or webp"),
                 require_base64: bool = Form(default=False, description="Return base64 data of generated image"),
                 async_process: bool = Form(default=False, description="Set to true will run async and return job info for retrieve generataion result later"),
                 ):
@@ -376,7 +381,7 @@ def as_form(cls, input_image: UploadFile = Form(File(None), description="Init im
                    performance_selection=performance_selection, aspect_ratios_selection=aspect_ratios_selection,
                    image_number=image_number, image_seed=image_seed, sharpness=sharpness, guidance_scale=guidance_scale,
                    base_model_name=base_model_name, refiner_model_name=refiner_model_name, refiner_switch=refiner_switch,
-                   loras=loras_model, advanced_params=advanced_params_obj, require_base64=require_base64, async_process=async_process)
+                   loras=loras_model, advanced_params=advanced_params_obj, save_extension=save_extension, require_base64=require_base64, async_process=async_process)
 
 
 class GeneratedImageResult(BaseModel):

fooocusapi/parameters.py

@@ -101,6 +101,7 @@ def __init__(self, prompt: str,
                  inpaint_additional_prompt: str | None,
                  image_prompts: List[Tuple[np.ndarray, float, float, str]],
                  advanced_params: List[any] | None,
+                 save_extension: str,
                  require_base64: bool):
         self.prompt = prompt
         self.negative_prompt = negative_prompt
@@ -126,6 +127,7 @@ def __init__(self, prompt: str,
         self.inpaint_input_image = inpaint_input_image
         self.inpaint_additional_prompt = inpaint_additional_prompt
         self.image_prompts = image_prompts
+        self.save_extension = save_extension
         self.require_base64 = require_base64
 
         if advanced_params is None:

fooocusapi/worker.py

@@ -100,14 +100,14 @@ def progressbar(_, number, text):
         print(f'[Fooocus] {text}')
         outputs.append(['preview', (number, text, None)])
 
-    def yield_result(_, imgs, tasks):
+    def yield_result(_, imgs, tasks, extension='png'):
         if not isinstance(imgs, list):
             imgs = [imgs]
 
         results = []
         for i, im in enumerate(imgs):
             seed = -1 if len(tasks) == 0 else tasks[i]['task_seed']
-            img_filename = save_output_file(im)
+            img_filename = save_output_file(img=im, extension=extension)
             results.append(ImageGenerationResult(im=img_filename, seed=str(seed), finish_reason=GenerationFinishReason.success))
         async_task.set_result(results, False)
         worker_queue.finish_task(async_task.job_id)
@@ -150,6 +150,7 @@ def yield_result(_, imgs, tasks):
         inpaint_input_image = params.inpaint_input_image
         inpaint_additional_prompt = params.inpaint_additional_prompt
         inpaint_mask_image_upload = None
+        save_extension = params.save_extension
 
         if inpaint_additional_prompt is None:
             inpaint_additional_prompt = ''
@@ -547,7 +548,7 @@ def yield_result(_, imgs, tasks):
             if direct_return:
                 d = [('Upscale (Fast)', '2x')]
                 log(uov_input_image, d)
-                yield_result(async_task, uov_input_image, tasks)
+                yield_result(async_task, uov_input_image, tasks, save_extension)
                 return
 
             tiled = True
@@ -693,7 +694,7 @@ def yield_result(_, imgs, tasks):
                 cn_img = HWC3(cn_img)
                 task[0] = core.numpy_to_pytorch(cn_img)
                 if advanced_parameters.debugging_cn_preprocessor:
-                    yield_result(async_task, cn_img, tasks)
+                    yield_result(async_task, cn_img, tasks, save_extension)
                     return
             for task in cn_tasks[flags.cn_cpds]:
                 cn_img, cn_stop, cn_weight = task
@@ -705,7 +706,7 @@ def yield_result(_, imgs, tasks):
                 cn_img = HWC3(cn_img)
                 task[0] = core.numpy_to_pytorch(cn_img)
                 if advanced_parameters.debugging_cn_preprocessor:
-                    yield_result(async_task, cn_img, tasks)
+                    yield_result(async_task, cn_img, tasks, save_extension)
                     return
             for task in cn_tasks[flags.cn_ip]:
                 cn_img, cn_stop, cn_weight = task
@@ -716,7 +717,7 @@ def yield_result(_, imgs, tasks):
 
                 task[0] = ip_adapter.preprocess(cn_img, ip_adapter_path=ip_adapter_path)
                 if advanced_parameters.debugging_cn_preprocessor:
-                    yield_result(async_task, cn_img, tasks)
+                    yield_result(async_task, cn_img, tasks, save_extension)
                     return
             for task in cn_tasks[flags.cn_ip_face]:
                 cn_img, cn_stop, cn_weight = task
@@ -730,7 +731,7 @@ def yield_result(_, imgs, tasks):
 
                 task[0] = ip_adapter.preprocess(cn_img, ip_adapter_path=ip_adapter_face_path)
                 if advanced_parameters.debugging_cn_preprocessor:
-                    yield_result(async_task, cn_img, tasks)
+                    yield_result(async_task, cn_img, tasks, save_extension)
                     return
 
             all_ip_tasks = cn_tasks[flags.cn_ip] + cn_tasks[flags.cn_ip_face]
@@ -877,7 +878,7 @@ def callback(step, x0, x, total_steps, y):
         if async_task.finish_with_error:
             worker_queue.finish_task(async_task.job_id)
             return async_task.task_result
-        yield_result(None, results, tasks)
+        yield_result(None, results, tasks, save_extension)
         return
     except Exception as e:
         print('Worker error:', e)