diff --git a/.gitattributes b/.gitattributes
index a6344aac8c09253b3b630fb776ae94478aa0275b..dd04d6a78d02f75aee556e4fee410d58b3cf1d37 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text
+assets/banner/banner.png filter=lfs diff=lfs merge=lfs -text
+assets/banner/thumbnail.png filter=lfs diff=lfs merge=lfs -text
+assets/examples/11_layout.png filter=lfs diff=lfs merge=lfs -text
+assets/image_gallery_en/-017.jpg filter=lfs diff=lfs merge=lfs -text
+assets/image_gallery_en/062.jpg filter=lfs diff=lfs merge=lfs -text
+assets/ttf/AlibabaPuHuiTi-2-55-Regular.ttf filter=lfs diff=lfs merge=lfs -text
diff --git a/app.py b/app.py
new file mode 100644
index 0000000000000000000000000000000000000000..5bddccb4256b5dce3b2c90f2d30f179ac675b45c
--- /dev/null
+++ b/app.py
@@ -0,0 +1,388 @@
+##!/usr/bin/python3
+# -*- coding: utf-8 -*-
+# @Time : 2024-01-29
+# @Author : Junjie He
+import json
+import os
+import time
+import uuid
+
+import cv2
+import gradio as gr
+import numpy as np
+from PIL import Image
+from modelscope.outputs import OutputKeys
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+from src.generation import call_generation
+from src.util import upload_np_2_oss, upload_json_string_2_oss, upload_preprocess, merge_images
+
+universal_matting = pipeline(Tasks.universal_matting, model='damo/cv_unet_universal-matting')
+
+img = "assets/image_gallery_en/"
+files = os.listdir(img)
+files = [file for file in files if file.lower().endswith(('.png', '.jpg', '.jpeg'))]
+files = sorted(files)
+basic_usage = []
+showcases = []
+for idx, name in enumerate(files):
+ temp = os.path.join(os.path.dirname(__file__), img, name)
+ if idx < 4:
+ basic_usage.append(temp)
+ else:
+ showcases.append(temp)
+
+# - - - - - examples - - - - - #
+ep = "assets/examples"
+# Layout, Style, Color, Subject, Prompt，Strict Layout Edge，Layout Content Scale, Automatic Image Matting
+image_examples = [
+ [0, f"{ep}/00_layout.png", f"{ep}/empty.png", f"{ep}/empty.png", f"{ep}/empty.png", "", True, 0., False],
+ [1, f"{ep}/01_layout.png", f"{ep}/empty.png", f"{ep}/empty.png", f"{ep}/empty.png", "", True, 0.8, False],
+ [2, f"{ep}/empty.png", f"{ep}/02_style.png", f"{ep}/empty.png", f"{ep}/empty.png", "", True, 0.8, False],
+ [3, f"{ep}/empty.png", f"{ep}/03_style.png", f"{ep}/empty.png", f"{ep}/empty.png", "", True, 0.8, False],
+ [4, f"{ep}/empty.png", f"{ep}/empty.png", f"{ep}/04_color.png", f"{ep}/empty.png", "A moose, Merry Christmas", True, 0.8, False],
+ [5, f"{ep}/empty.png", f"{ep}/empty.png", f"{ep}/05_color.png", f"{ep}/empty.png", "A photo about cherry blossom",
+ True, 0.8, False],
+ [6, f"{ep}/06_layout.png", f"{ep}/06_style.jpeg", f"{ep}/empty.png", f"{ep}/empty.png", "", True, 0.8, False],
+ [7, f"{ep}/07_layout.jpeg", f"{ep}/07_style.jpeg", f"{ep}/empty.png", f"{ep}/empty.png", "", True, 0.8, False],
+ [8, f"{ep}/empty.png", f"{ep}/08_style.png", f"{ep}/08_color.jpeg", f"{ep}/empty.png", "", True, 0.8, False],
+ [9, f"{ep}/empty.png", f"{ep}/09_style.png", f"{ep}/empty.png", f"{ep}/base_image1.jpeg", "", True, 0.8, True],
+ [10, f"{ep}/10_layout.png", f"{ep}/10_style.png", f"{ep}/empty.png", f"{ep}/base_image2.png", "", True, 0.8, False],
+ [11, f"{ep}/11_layout.png", f"{ep}/empty.png", f"{ep}/empty.png", f"{ep}/base_image4.png", "", False, 0.8, False],
+ [12, f"{ep}/12_layout.png", f"{ep}/empty.png", f"{ep}/empty.png", f"{ep}/base_image3.png", "", False, 0.8, False],
+]
+
+example_images = [
+ [0, f"{ep}/layout_image1.jpeg", None, None, None],
+ [1, f"{ep}/layout_image1.jpeg", None, None, None],
+ [2, None, f"{ep}/style_image1.jpeg", None, None],
+ [3, None, f"{ep}/style_image1.jpeg", None, None],
+ [4, None, None, f"{ep}/color_image1.jpeg", None],
+ [5, None, None, f"{ep}/color_image3.jpeg", None],
+ [6, f"{ep}/layout_image2.jpeg", f"{ep}/style_image2.jpeg", None, None],
+ [7, f"{ep}/layout_image3.jpeg", f"{ep}/style_image3.jpeg", None, None],
+ [8, None, f"{ep}/style_image4.jpeg", f"{ep}/color_image2.jpeg", None],
+ [9, None, f"{ep}/style_image6.jpeg", None, f"{ep}/09_base.png"],
+ [10, f"{ep}/layout_image5.jpeg", f"{ep}/style_image5.jpeg", None, f"{ep}/10_base.png"],
+ [11, f"{ep}/layout_image7.jpeg", None, None, f"{ep}/11_base.png"],
+ [12, f"{ep}/layout_image6.jpeg", None, None, f"{ep}/12_base.png"],
+]
+
+example_masks = [
+ [0, None, None, None],
+ [1, f"{ep}/layout_image1_mask.png", None, None],
+ [2, None, f"{ep}/style_image1_mask.png", None],
+ [3, None, f"{ep}/style_image1_mask2.png", None],
+ [4, None, None, None],
+ [5, None, None, f"{ep}/color_image3_mask.png"],
+ [6, None, None, None],
+ [7, None, None, None],
+ [8, None, None, None],
+ [9, None, f"{ep}/style_image6_mask.png", None],
+ [10, f"{ep}/layout_image5_mask.png", None, None],
+ [11, None, None, None],
+ [12, f"{ep}/layout_image6_mask.png", None, None],
+]
+
+
+def process_example(example_idx, pil_layout_image, pil_style_image, pil_color_image, pil_base_image_rgba,
+ prompt, strict_edge, layout_scale, preprocess_base_image):
+ _, layout_image, style_image, color_image, base_image_rgba = example_images[example_idx]
+ _, layout_mask, style_mask, color_mask = example_masks[example_idx]
+
+ pil_layout_image = None if layout_image is None else pil_layout_image
+ pil_style_image = None if style_image is None else pil_style_image
+ pil_color_image = None if color_image is None else pil_color_image
+ pil_base_image_rgba = None if base_image_rgba is None else pil_base_image_rgba
+
+ return pil_layout_image, layout_mask, pil_style_image, style_mask, pil_color_image, color_mask, \
+ pil_base_image_rgba, prompt, strict_edge, layout_scale, preprocess_base_image
+
+
+def process(pil_base_image_rgba=None, preprocess_base_image=False,
+ pil_layout_image_dict=None, layout_scale=1.0, edge_consistency=0.5,
+ strict_edge=False,
+ pil_color_image_dict=None, color_scale=1.0,
+ pil_style_image_dict=None, style_scale=1.0, prompt="best quality", negative_prompt="",
+ pil_layout_mask=None, pil_style_mask=None, pil_color_mask=None):
+ request_id = time.strftime('%Y%m%d-', time.localtime(time.time())) + str(uuid.uuid4())
+
+ output_aspect_ratio = 1.
+ matting_flag = False
+
+ if pil_base_image_rgba is None:
+ base_image_url = ""
+ pil_fg_mask = None
+ else:
+ if preprocess_base_image:
+ matting_flag = True
+ orig_image = np.array(pil_base_image_rgba)
+ orig_alpha = np.array(pil_base_image_rgba)[..., -1]
+ matting_alpha = universal_matting(pil_base_image_rgba)[OutputKeys.OUTPUT_IMG][..., -1]
+ orig_image[..., -1] = ((matting_alpha > 200) * (orig_alpha > 200) * 255.).astype(np.uint8)
+ pil_base_image_rgba = Image.fromarray(orig_image)
+ pil_fg_mask = pil_base_image_rgba.split()[-1]
+
+ w, h = pil_base_image_rgba.size
+ output_aspect_ratio = max(1.0 * w / h, 1.0 * h / w)
+ if output_aspect_ratio > 2:
+ raise gr.Error("Input of subject images with aspect ratio exceeding 2 is not supported")
+ if min(w, h) > 1536:
+ raise gr.Error("Input of subject images with the shorter side exceeding 1536 pixels is not supported")
+ base_image_url = upload_np_2_oss(np.array(pil_base_image_rgba), request_id + "_base.png")
+
+ if pil_layout_image_dict is None:
+ layout_image_url = ""
+ else:
+ np_layout_image = np.array(pil_layout_image_dict["image"].convert("RGBA"))
+ np_layout_image, np_layout_alpha = np_layout_image[..., :3], np_layout_image[..., 3]
+ np_layout_mask = np.array(pil_layout_image_dict["mask"].convert("L"))
+ if pil_layout_mask is None:
+ np_layout_mask = ((np_layout_alpha > 127) * (np_layout_mask < 127) * 255.).astype(np.uint8)
+ else:
+ np_layout_mask = ((np_layout_alpha > 127) * (np_layout_mask < 127) *
+ (np.array(pil_layout_mask) > 127) * 255.).astype(np.uint8)
+ layout_image_url = upload_np_2_oss(
+ np.concatenate([np_layout_image, np_layout_mask[..., None]], axis=-1), request_id + "_layout.png"
+ )
+ if pil_base_image_rgba is None:
+ h, w, c = np_layout_image.shape
+ output_aspect_ratio = max(1.0 * w / h, 1.0 * h / w)
+ if output_aspect_ratio > 2:
+ raise gr.Error("Input of layout images with aspect ratio exceeding 2 is not supported")
+ if min(w, h) > 1536:
+ raise gr.Error("Input of layout images with the shorter side exceeding 1536 pixels is not supported")
+
+ if pil_style_image_dict is None:
+ style_image_url = ""
+ else:
+ np_style_image = np.array(pil_style_image_dict["image"].convert("RGBA"))
+ np_style_image, np_style_alpha = np_style_image[..., :3], np_style_image[..., 3]
+ np_style_mask = np.array(pil_style_image_dict["mask"].convert("L"))
+ if pil_style_mask is None:
+ np_style_mask = ((np_style_alpha > 127) * (np_style_mask < 127) * 255.).astype(np.uint8)
+ else:
+ np_style_mask = ((np_style_alpha > 127) * (np_style_mask < 127) *
+ (np.array(pil_style_mask) > 127) * 255.).astype(np.uint8)
+ style_image_url = upload_np_2_oss(
+ np.concatenate([np_style_image, np_style_mask[..., None]], axis=-1), request_id + "_style.png"
+ )
+
+ if pil_color_image_dict is None:
+ color_image_url = ""
+ else:
+ np_color_image = np.array(pil_color_image_dict["image"].convert("RGBA"))
+ np_color_image, np_color_alpha = np_color_image[..., :3], np_color_image[..., 3]
+ np_color_mask = np.array(pil_color_image_dict["mask"].convert("L"))
+ if pil_color_mask is None:
+ np_color_mask = ((np_color_alpha > 127) * (np_color_mask < 127) * 255.).astype(np.uint8)
+ else:
+ np_color_mask = ((np_color_alpha > 127) * (np_color_mask < 127) *
+ (np.array(pil_color_mask) > 127) * 255.).astype(np.uint8)
+ color_image_url = upload_np_2_oss(
+ np.concatenate([np_color_image, np_color_mask[..., None]], axis=-1), request_id + "_color.png"
+ )
+
+ res = call_generation(base_image_url=base_image_url, layout_image_url=layout_image_url,
+ color_image_url=color_image_url, style_image_url=style_image_url,
+ strict_edge=int(strict_edge), layout_scale=int(layout_scale * 10),
+ edge_consistency=int(edge_consistency * 10), color_scale=int(color_scale * 10),
+ style_scale=int(style_scale * 10), prompt=prompt, negative_prompt=negative_prompt,
+ output_aspect_ratio=output_aspect_ratio)
+
+ for idx, r in enumerate(res):
+ upload_np_2_oss(np.array(r), request_id + f"_{idx}.jpg")
+
+ if matting_flag:
+ res.append(pil_base_image_rgba)
+ return res, request_id, True, pil_fg_mask
+
+
+if __name__ == "__main__":
+
+ block = gr.Blocks(
+ title="TransferAnything",
+ css="assets/css/style.css",
+ theme=gr.themes.Soft(
+ radius_size=gr.themes.sizes.radius_none,
+ text_size=gr.themes.sizes.text_md
+ )).queue(concurrency_count=3)
+ with block:
+ with gr.Row():
+ with gr.Column():
+ gr.HTML(f"""
+
+
TransferAnything: Enabling Versatile Visual Information Transfer for Creative Image Synthesis
+
+
+
+
+
TransferAnything supports transferring various visual information from any area of any image to create new compositions, offering higher freedom and flexibility in image synthesis. Currently, it supports the transfer of layout, color, style, and pixel content, with more visual information transfer capabilities under continuous development.
+
+
如果你认为该项目有所帮助的话，不妨给我们Github点个Star以便获取最新的项目进展.
+ with gr.Tabs(elem_classes=["Tab"]):
+ with gr.TabItem("Image Gallery"):
+ gr.Gallery(label="Basic Usage", value=basic_usage, height=320, columns=4, object_fit="scale-down")
+ gr.Gallery(label="Advanced Combinations", value=showcases, height=800, columns=4, object_fit="scale-down")
+ with gr.TabItem("Image Creation"):
+ with gr.Row():
+ with gr.Column(scale=1):
+ ...
+ with gr.Column(scale=3):
+ gr.Image(value="assets/banner/banner.png", width=1024, show_label=False,
+ show_download_button=False)
+ with gr.Column(scale=1):
+ ...
+ with gr.Accordion(label="🧭 Instructions:", open=True, elem_id="accordion"):
+ with gr.Row(equal_height=True):
+ # with gr.Row(elem_id="ShowCase"):
+ # gr.Image(value="assets/banner/ra.gif")
+ gr.Markdown("""
+ - ⭐️ step1： (Optional) Upload or select a set of images from the examples for the "Layout", "Style", and "Color" reference. Mix and match freely, no need to select all.
+ - ⭐️ step2： (Optional) Use brush to erase areas in the layout, style, and color reference images (if present) that you do not want transferred.
+ - ⭐️ step3： (Optional) Upload an image with the subject you wish to preserve at the pixel level to the "Subject" component, with a transparent channel required (or upload a regular RGB image and select automatic image matting, which will automatically segment the subject area for you).
+ - ⭐️ step4： Click "Run" to start the generation process.
+ - ⭐️ step5： (Optional) Additionally, prompt input is supported, as well as control over advanced parameters such as layout edge consistency and conditional weights. Feel free to try these features.
+ """)
+ # with gr.Row(equal_height=True):
+ # gr.Markdown("""❤️ 温馨提示：上传图片最大边不超过1024，宽高比为1：1，将会生成更快哟""")
+ with gr.Row():
+ with gr.Column(scale=1, min_width=160):
+ with gr.Tabs(elem_classes=["feedback"]):
+ with gr.TabItem("Layout (Optional)"):
+ pil_layout_image_dict = gr.ImageMask(source='upload', type="pil", show_label=False,
+ image_mode="RGBA")
+ pil_layout_image = gr.Image(interactive=False, type="pil", visible=False, label="Layout")
+ pil_layout_mask = gr.Image(interactive=False, type="pil", visible=False, label="Layout Mask",
+ image_mode="L")
+ with gr.Box():
+ with gr.Accordion(label="Layout Parameters", open=False, elem_id="accordion"):
+ with gr.TabItem("Layout Edge"):
+ strict_edge = gr.Checkbox(label="Strict", value=True)
+ strict_edge_mirror = gr.Checkbox(label="Strict Layout Edge", visible=False)
+ edge_consistency = gr.Slider(label="Degree of Consistency (If Not Strict)", minimum=0.0,
+ maximum=1.0,
+ step=0.1, value=0.8, interactive=True)
+ with gr.TabItem("Layout Content"):
+ layout_scale = gr.Slider(label="Scale", minimum=0.0, maximum=1.0, step=0.1,
+ value=0.8,
+ interactive=True)
+ layout_scale_mirror = gr.Slider(label="Layout Content Scale", visible=False)
+
+ with gr.Column(scale=1, min_width=160):
+ with gr.Tabs(elem_classes=["feedback"]):
+ with gr.TabItem("Style (Optional)"):
+ pil_style_image_dict = gr.ImageMask(source='upload', type="pil", show_label=False,
+ image_mode="RGBA")
+ pil_style_image = gr.Image(interactive=False, type="pil", visible=False, label="Style")
+ pil_style_mask = gr.Image(interactive=False, type="pil", visible=False, label="Style Mask",
+ image_mode="L")
+ with gr.Box():
+ with gr.Accordion(label="Style Parameters", open=False, elem_id="accordion"):
+ style_scale = gr.Slider(label="Scale", minimum=0.0, maximum=1.0, step=0.1,
+ value=0.8, interactive=True)
+ with gr.Column(scale=1, min_width=160):
+ with gr.Tabs(elem_classes=["feedback"]):
+ with gr.TabItem("Color (Optional, recommended for use with prompt)"):
+ pil_color_image_dict = gr.ImageMask(source='upload', type="pil", show_label=False,
+ image_mode="RGBA")
+ pil_color_image = gr.Image(interactive=False, type="pil", visible=False, label="Color")
+ pil_color_mask = gr.Image(interactive=False, type="pil", visible=False, label="Color Mask",
+ image_mode="L")
+ with gr.Box():
+ with gr.Accordion(label="Color Parameters", open=False, elem_id="accordion"):
+ color_scale = gr.Slider(label="Scale", minimum=0.0, maximum=1.0, step=0.1,
+ value=0.8, interactive=True)
+ with gr.Row():
+ with gr.Column(scale=1, min_width=160):
+ with gr.Tabs(elem_classes=["feedback"]):
+ with gr.TabItem("Subject (Optional)"):
+ pil_base_image_rgba = gr.Image(source='upload',
+ interactive=True, show_label=False,
+ type="pil", image_mode="RGBA", tool="editor")
+ pil_base_image_rgba_mirror = gr.Image(label="Subject", image_mode="RGBA", visible=False)
+ with gr.Box():
+ preprocess_base_image = gr.Checkbox(label="Automatic Image Matting")
+ pil_fg_mask = gr.Image(interactive=False, type="pil", image_mode="L", visible=False)
+ run_button = gr.Button("Run", elem_id="btn")
+ with gr.Accordion("", open=True, elem_id="accordion1"):
+ prompt = gr.Textbox(value="", label='Prompt', lines=1, interactive=True)
+ prompt_mirror = gr.Textbox(label='Prompt', visible=False)
+ negative_prompt = gr.Textbox(value="", label='Negative prompt', lines=1,
+ interactive=True)
+ with gr.Column(scale=2, min_width=160):
+ with gr.Tabs(elem_classes=["feedback"]):
+ with gr.TabItem("Outputs"):
+ result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery",
+ preview=True)
+ recommend = gr.Button("Recommend results to Image Gallery", elem_id="recBut")
+ request_id = gr.State(value="")
+ gallery_flag = gr.State(value=False)
+ with gr.Row():
+ with gr.Box():
+ example_idx = gr.Slider(label="Index", visible=False, value=0)
+ example = gr.Examples(
+ label="Input Examples",
+ examples=image_examples,
+ inputs=[example_idx,
+ pil_layout_image, pil_style_image, pil_color_image, pil_base_image_rgba_mirror,
+ prompt_mirror, strict_edge_mirror, layout_scale_mirror, preprocess_base_image],
+ outputs=[pil_layout_image_dict, pil_layout_mask, pil_style_image_dict, pil_style_mask,
+ pil_color_image_dict, pil_color_mask, pil_base_image_rgba,
+ prompt, strict_edge, layout_scale, preprocess_base_image],
+ fn=process_example,
+ run_on_click=True,
+ examples_per_page=20
+ )
+
+
+ def upload_to_img_gallery(pil_base_image_rgba, pil_layout_image_dict, pil_style_image_dict,
+ pil_color_image_dict, pil_fg_mask, prompt, negative_prompt, res, re_id, flag,
+ strict_edge, edge_consistency, layout_scale, style_scale, color_scale,
+ preprocess_base_image):
+ if flag:
+ np_out_base_image, np_out_layout_image, np_out_style_image, np_out_color_image = upload_preprocess(
+ pil_base_image_rgba, pil_layout_image_dict, pil_style_image_dict, pil_color_image_dict, pil_fg_mask)
+ np_out_images = [np_out_base_image, np_out_layout_image, np_out_style_image, np_out_color_image]
+ for idx, r in enumerate(res):
+ if idx < 4:
+ r = cv2.imread(r['name'])
+ r = cv2.cvtColor(r, cv2.COLOR_BGR2RGB)
+ upload_np_2_oss(merge_images(*np_out_images, r, prompt, negative_prompt),
+ name=re_id + f"_merge_{idx}.jpg", gallery=True)
+ config = dict(
+ strict_edge=strict_edge,
+ edge_consistency=edge_consistency,
+ layout_scale=layout_scale,
+ style_scale=style_scale,
+ color_scale=color_scale,
+ preprocess_base_image=preprocess_base_image
+ )
+ upload_json_string_2_oss(json.dumps(config), name=re_id + f"_config.txt", gallery=True)
+
+ flag = False
+ gr.Info("Images have been uploaded and await review.")
+ else:
+ gr.Info("No images to recommend, or already suggested once.")
+ return flag
+
+
+ recommend.click(
+ upload_to_img_gallery,
+ [pil_base_image_rgba, pil_layout_image_dict, pil_style_image_dict, pil_color_image_dict, pil_fg_mask,
+ prompt, negative_prompt, result_gallery, request_id, gallery_flag, strict_edge, edge_consistency,
+ layout_scale, style_scale, color_scale, preprocess_base_image],
+ [gallery_flag]
+ )
+
+ ips = [pil_base_image_rgba, preprocess_base_image,
+ pil_layout_image_dict, layout_scale, edge_consistency, strict_edge,
+ pil_color_image_dict, color_scale,
+ pil_style_image_dict, style_scale, prompt, negative_prompt,
+ pil_layout_mask, pil_style_mask, pil_color_mask]
+ run_button.click(fn=process, inputs=ips, outputs=[result_gallery, request_id, gallery_flag, pil_fg_mask])
+
+ block.launch(server_name='0.0.0.0', share=False, server_port=7688)
diff --git a/assets/banner/banner.png b/assets/banner/banner.png
new file mode 100644
index 0000000000000000000000000000000000000000..f4d6d162ddfd10a34fcf5798fae9d137c33505d8
--- /dev/null
+++ b/assets/banner/banner.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4fd9d7b4d711f9dcc928876cbf3c303fd9c34b6d82123f2ca7078ae797108400
+size 1051123
diff --git a/assets/banner/thumbnail.png b/assets/banner/thumbnail.png
new file mode 100644
index 0000000000000000000000000000000000000000..5b0c730a732c0f998a2475badf99ae386e57f229
--- /dev/null
+++ b/assets/banner/thumbnail.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:03f0515be3f637da63e340f467a28fc98310d04d7e4748d2a597e7e211037a46
+size 3178964
diff --git a/assets/css/style.css b/assets/css/style.css
new file mode 100644
index 0000000000000000000000000000000000000000..cbb014dc4d792f94df526411281dc16d31a2985a
--- /dev/null
+++ b/assets/css/style.css
@@ -0,0 +1,71 @@
+
+.baselayout {
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diff --git a/assets/ttf/AlibabaPuHuiTi-2-55-Regular.ttf b/assets/ttf/AlibabaPuHuiTi-2-55-Regular.ttf
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+version https://git-lfs.github.com/spec/v1
+oid sha256:a22ad467d9d6b4c9a0b2e033927ed41592743c987546a7397215ce96b850743b
+size 8449680
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9d46b3678057352bd2390c2c2882f51a9211b125
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,3 @@
+dashscope
+modelscope[cv] -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
+tensorflow-gpu==2.11.0
diff --git a/src/__init__.py b/src/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/src/generation.py b/src/generation.py
new file mode 100644
index 0000000000000000000000000000000000000000..3e2e2100bcda8e90c271aec148218deb49c63fa8
--- /dev/null
+++ b/src/generation.py
@@ -0,0 +1,101 @@
+import json
+import os
+import time
+
+import gradio as gr
+import requests
+
+from src.log import logger
+from src.util import download_images
+
+
+def call_generation(base_image_url="", layout_image_url="", color_image_url="", style_image_url="",
+ strict_edge=0, layout_scale=8, edge_consistency=8, color_scale=8,
+ style_scale=8, prompt="", negative_prompt="", output_aspect_ratio=1.0):
+ API_KEY = os.getenv("API_KEY_BG_GENERATION")
+ if output_aspect_ratio >= 1:
+ BATCH_SIZE = 2
+ REPEAT = 2
+ else:
+ BATCH_SIZE = 4
+ REPEAT = 1
+ headers = {
+ "Content-Type": "application/json",
+ "Accept": "application/json",
+ "Authorization": f"Bearer {API_KEY}",
+ "X-DashScope-Async": "enable",
+ }
+ data = {
+ "model": "wanx-poster-imitation-v1",
+ "input": {
+ "base_image_url": base_image_url,
+ "layout_image_url": layout_image_url,
+ "color_image_url": color_image_url,
+ "style_image_url": style_image_url,
+ "prompt": prompt,
+ "negative_prompt": negative_prompt,
+ },
+ "parameters": {
+ "strict_layout": strict_edge,
+ "layout_scale": layout_scale,
+ "layout_spatial_consistency": edge_consistency,
+ "color_scale": color_scale,
+ "style_scale": style_scale,
+ "n": BATCH_SIZE
+ }
+ }
+ url_create_task = 'https://dashscope.aliyuncs.com/api/v1/services/aigc/poster-imitation/generation'
+
+ all_res_ = []
+ for _ in range(REPEAT):
+ res_ = requests.post(url_create_task, data=json.dumps(data), headers=headers)
+ all_res_.append(res_)
+
+ all_image_data = []
+ for res_ in all_res_:
+ respose_code = res_.status_code
+ if 200 == respose_code:
+ res = json.loads(res_.content.decode())
+ request_id = res['request_id']
+ task_id = res['output']['task_id']
+ logger.info(f"task_id: {task_id}: Create Poster Imitation request success. Params: {data}")
+
+ # 异步查询
+ is_running = True
+ while is_running:
+ url_query = f'https://dashscope.aliyuncs.com/api/v1/tasks/{task_id}'
+ res_ = requests.post(url_query, headers=headers)
+ respose_code = res_.status_code
+ if 200 == respose_code:
+ res = json.loads(res_.content.decode())
+ if "SUCCEEDED" == res['output']['task_status']:
+ logger.info(f"task_id: {task_id}: Generation task query success.")
+ results = res['output']['results']
+ img_urls = [x['url'] for x in results]
+ logger.info(f"task_id: {task_id}: {res}")
+ break
+ elif "FAILED" != res['output']['task_status']:
+ logger.debug(f"task_id: {task_id}: query result...")
+ time.sleep(1)
+ else:
+ raise gr.Error('Fail to get results from Generation task.')
+
+ else:
+ logger.error(f'task_id: {task_id}: Fail to query task result: {res_.content}')
+ raise gr.Error("Fail to query task result.")
+
+ logger.info(f"task_id: {task_id}: download generated images.")
+ img_data = download_images(img_urls, BATCH_SIZE)
+ logger.info(f"task_id: {task_id}: Generate done.")
+ all_image_data += img_data
+ else:
+ logger.error(f'Fail to create Generation task: {res_.content}')
+ raise gr.Error("Fail to create Generation task.")
+
+ if len(all_image_data) != REPEAT * BATCH_SIZE:
+ raise gr.Error("Fail to Generation.")
+ return all_image_data
+
+
+if __name__ == "__main__":
+ call_generation()
diff --git a/src/log.py b/src/log.py
new file mode 100644
index 0000000000000000000000000000000000000000..044070382a8577aea1ec5f05d3d7681ae94feff1
--- /dev/null
+++ b/src/log.py
@@ -0,0 +1,18 @@
+import logging
+import os
+from logging.handlers import RotatingFileHandler
+
+log_file_name = "workdir/log_transferAnything.log"
+os.makedirs(os.path.dirname(log_file_name), exist_ok=True)
+
+format = '[%(levelname)s] %(asctime)s "%(filename)s", line %(lineno)d, %(message)s'
+logging.basicConfig(
+ format=format,
+ datefmt="%Y-%m-%d %H:%M:%S",
+ level=logging.INFO)
+logger = logging.getLogger(name="WordArt_Studio")
+
+fh = RotatingFileHandler(log_file_name, maxBytes=20000000, backupCount=3)
+formatter = logging.Formatter(format, datefmt="%Y-%m-%d %H:%M:%S")
+fh.setFormatter(formatter)
+logger.addHandler(fh)
diff --git a/src/util.py b/src/util.py
new file mode 100644
index 0000000000000000000000000000000000000000..5b8bb9deea307659f76088e0770c86392b98c6de
--- /dev/null
+++ b/src/util.py
@@ -0,0 +1,251 @@
+import concurrent.futures
+import io
+import os
+
+import numpy as np
+import oss2
+import requests
+from PIL import Image, ImageDraw, ImageFont
+
+from .log import logger
+
+# oss
+access_key_id = os.getenv("ACCESS_KEY_ID")
+access_key_secret = os.getenv("ACCESS_KEY_SECRET")
+bucket_name = os.getenv("BUCKET_NAME")
+endpoint = os.getenv("ENDPOINT")
+
+bucket = oss2.Bucket(oss2.Auth(access_key_id, access_key_secret), endpoint, bucket_name)
+oss_path = "hejunjie.hjj/TransferAnythingHF"
+oss_path_img_gallery = "hejunjie.hjj/TransferAnythingHF_img_gallery"
+
+
+def download_img_pil(index, img_url):
+ # print(img_url)
+ r = requests.get(img_url, stream=True)
+ if r.status_code == 200:
+ img = Image.open(io.BytesIO(r.content))
+ return (index, img)
+ else:
+ logger.error(f"Fail to download: {img_url}")
+
+
+def download_images(img_urls, batch_size):
+ imgs_pil = [None] * batch_size
+ # worker_results = []
+ with concurrent.futures.ThreadPoolExecutor(max_workers=4) as executor:
+ to_do = []
+ for i, url in enumerate(img_urls):
+ future = executor.submit(download_img_pil, i, url)
+ to_do.append(future)
+
+ for future in concurrent.futures.as_completed(to_do):
+ ret = future.result()
+ # worker_results.append(ret)
+ index, img_pil = ret
+ imgs_pil[index] = img_pil # 按顺序排列url，后续下载关联的图片或者svg需要使用
+
+ return imgs_pil
+
+
+def upload_np_2_oss(input_image, name="cache.png", gallery=False):
+ assert name.lower().endswith((".png", ".jpg")), name
+ imgByteArr = io.BytesIO()
+ if name.lower().endswith(".png"):
+ Image.fromarray(input_image).save(imgByteArr, format="PNG")
+ else:
+ Image.fromarray(input_image).save(imgByteArr, format="JPEG", quality=95)
+ imgByteArr = imgByteArr.getvalue()
+
+ if gallery:
+ path = oss_path_img_gallery
+ else:
+ path = oss_path
+
+ bucket.put_object(path + "/" + name, imgByteArr) # data为数据，可以是图片
+ ret = bucket.sign_url('GET', path + "/" + name, 60 * 60 * 24) # 返回值为链接，参数依次为，方法/oss上文件路径/过期时间(s)
+ del imgByteArr
+ return ret
+
+
+def upload_json_string_2_oss(jsonStr, name="cache.txt", gallery=False):
+ if gallery:
+ path = oss_path_img_gallery
+ else:
+ path = oss_path
+
+ bucket.put_object(path + "/" + name, bytes(jsonStr, "utf-8")) # data为数据
+ ret = bucket.sign_url('GET', path + "/" + name, 60 * 60 * 24) # 返回值为链接，参数依次为，方法/oss上文件路径/过期时间(s)
+ return ret
+
+
+def upload_preprocess(pil_base_image_rgba, pil_layout_image_dict, pil_style_image_dict, pil_color_image_dict,
+ pil_fg_mask):
+ np_out_base_image = np_out_layout_image = np_out_style_image = np_out_color_image = None
+
+ if pil_base_image_rgba is not None:
+ np_fg_image = np.array(pil_base_image_rgba)[..., :3]
+ np_fg_mask = np.expand_dims(np.array(pil_fg_mask).astype(float), axis=-1) / 255.
+ np_fg_mask = np_fg_mask * 0.5 + 0.5
+ np_out_base_image = (np_fg_image * np_fg_mask + (1 - np_fg_mask) * np.array([0, 0, 255])).round().clip(0,
+ 255).astype(
+ np.uint8)
+
+ if pil_layout_image_dict is not None:
+ np_layout_image = np.array(pil_layout_image_dict["image"].convert("RGBA"))
+ np_layout_image, np_layout_alpha = np_layout_image[..., :3], np_layout_image[..., 3]
+ np_layout_mask = np.array(pil_layout_image_dict["mask"].convert("L"))
+ np_layout_mask = ((np_layout_alpha > 127) * (np_layout_mask < 127)).astype(float)[..., None]
+ np_layout_mask = np_layout_mask * 0.5 + 0.5
+ np_out_layout_image = (
+ np_layout_image * np_layout_mask + (1 - np_layout_mask) * np.array([0, 0, 255])).round().clip(0,
+ 255).astype(
+ np.uint8)
+
+ if pil_style_image_dict is not None:
+ np_style_image = np.array(pil_style_image_dict["image"].convert("RGBA"))
+ np_style_image, np_style_alpha = np_style_image[..., :3], np_style_image[..., 3]
+ np_style_mask = np.array(pil_style_image_dict["mask"].convert("L"))
+ np_style_mask = ((np_style_alpha > 127) * (np_style_mask < 127)).astype(float)[..., None]
+ np_style_mask = np_style_mask * 0.5 + 0.5
+ np_out_style_image = (
+ np_style_image * np_style_mask + (1 - np_style_mask) * np.array([0, 0, 255])).round().clip(0,
+ 255).astype(
+ np.uint8)
+
+ if pil_color_image_dict is not None:
+ np_color_image = np.array(pil_color_image_dict["image"].convert("RGBA"))
+ np_color_image, np_color_alpha = np_color_image[..., :3], np_color_image[..., 3]
+ np_color_mask = np.array(pil_color_image_dict["mask"].convert("L"))
+ np_color_mask = ((np_color_alpha > 127) * (np_color_mask < 127)).astype(float)[..., None]
+ np_color_mask = np_color_mask * 0.5 + 0.5
+ np_out_color_image = (
+ np_color_image * np_color_mask + (1 - np_color_mask) * np.array([0, 0, 255])).round().clip(0,
+ 255).astype(
+ np.uint8)
+
+ return np_out_base_image, np_out_layout_image, np_out_style_image, np_out_color_image
+
+
+def pad_image(image, target_size):
+ iw, ih = image.size # 原始图像的尺寸
+ w, h = target_size # 目标图像的尺寸
+ scale = min(w / iw, h / ih) # 转换的最小比例
+ # 保证长或宽，至少一个符合目标图像的尺寸 0.5保证四舍五入
+ nw = int(iw * scale + 0.5)
+ nh = int(ih * scale + 0.5)
+ image = image.resize((nw, nh), Image.BICUBIC) # 更改图像尺寸，双立法插值效果很好
+ new_image = Image.new('RGB', target_size, (255, 255, 255)) # 生成白色图像
+ new_image.paste(image, ((w - nw) // 2, (h - nh) // 2)) # 将图像填充为中间图像，两侧为黑色的样式
+ return new_image
+
+
+def add_text(image, text):
+ w, h = image.size
+ text_image = image.copy()
+ text_image_draw = ImageDraw.Draw(text_image)
+
+ ttf = ImageFont.truetype("assets/ttf/AlibabaPuHuiTi-2-55-Regular.ttf", int(h / 10))
+ left, top, right, bottom = ttf.getbbox(text)
+ text_image_draw.rectangle((0, 0, right + left, bottom + top), fill=(255, 255, 255))
+
+ image = Image.blend(image, text_image, 0.5)
+
+ image_draw = ImageDraw.Draw(image)
+ fillColor = (0, 0, 0, 255) # 文字颜色：黑色
+ pos = (0, 0) # 文本左上角位置 (离左边界距离， 离上边界距离)
+ image_draw.text(pos, text, font=ttf, fill=fillColor)
+ return image.convert("RGB")
+
+
+def compose_image(image_list, text_list, pil_size, nrow, ncol):
+ w, h = pil_size # 每张小图片大小
+
+ if len(image_list) > nrow * ncol:
+ raise ValueError("合成图片的参数和要求的数量不能匹配！")
+
+ assert len(image_list) == len(text_list)
+ new_image_list = []
+ new_text_list = []
+ for image, text in zip(image_list, text_list):
+ if image is not None:
+ new_image_list.append(image)
+ new_text_list.append(text)
+ if len(new_image_list) == 1:
+ ncol = nrow = 1
+ to_image = Image.new('RGB', (ncol * w, nrow * h), (255, 255, 255)) # 创建一个新图
+ for y in range(1, nrow + 1):
+ for x in range(1, ncol + 1):
+ if ncol * (y - 1) + x - 1 < len(new_image_list):
+ from_image = new_image_list[ncol * (y - 1) + x - 1].resize((w, h), Image.BICUBIC)
+ from_text = new_text_list[ncol * (y - 1) + x - 1]
+ if from_text is not None:
+ from_image = add_text(from_image, from_text)
+ to_image.paste(from_image, ((x - 1) * w, (y - 1) * h))
+ return to_image
+
+
+def split_text_lines(text, max_w, ttf):
+ text_split_lines = []
+ text_h = 0
+ if text != "":
+ line_start = 0
+ while line_start < len(text):
+ line_count = 0
+ _, _, right, bottom = ttf.getbbox(text[line_start: line_start + line_count + 1])
+ while right < max_w and line_count < len(text):
+ line_count += 1
+ _, _, right, bottom = ttf.getbbox(text[line_start: line_start + line_count + 1])
+ text_split_lines.append(text[line_start:line_start + line_count])
+ text_h += bottom
+ line_start += line_count
+ return text_split_lines, text_h
+
+
+def add_prompt(image, prompt, negative_prompt):
+ if prompt == "" and negative_prompt == "":
+ return image
+ if prompt != "":
+ prompt = "Prompt: " + prompt
+ if negative_prompt != "":
+ negative_prompt = "Negative prompt: " + negative_prompt
+
+ w, h = image.size
+
+ ttf = ImageFont.truetype("assets/ttf/AlibabaPuHuiTi-2-55-Regular.ttf", int(h / 20))
+
+ prompt_split_lines, prompt_h = split_text_lines(prompt, w, ttf)
+ negative_prompt_split_lines, negative_prompt_h = split_text_lines(negative_prompt, w, ttf)
+ text_h = prompt_h + negative_prompt_h
+ text = "\n".join(prompt_split_lines + negative_prompt_split_lines)
+ text_image = Image.new(image.mode, (w, text_h), color=(255, 255, 255))
+ text_image_draw = ImageDraw.Draw(text_image)
+ text_image_draw.text((0, 0), text, font=ttf, fill=(0, 0, 0))
+
+ out_image = Image.new(image.mode, (w, h + text_h), color=(255, 255, 255))
+ out_image.paste(image, (0, 0))
+ out_image.paste(text_image, (0, h))
+
+ return out_image
+
+
+def merge_images(np_fg_image, np_layout_image, np_style_image, np_color_image, np_res_image, prompt, negative_prompt):
+ pil_res_image = Image.fromarray(np_res_image)
+
+ w, h = pil_res_image.size
+ pil_fg_image = None if np_fg_image is None else pad_image(Image.fromarray(np_fg_image), (w, h))
+ pil_layout_image = None if np_layout_image is None else pad_image(Image.fromarray(np_layout_image), (w, h))
+ pil_style_image = None if np_style_image is None else pad_image(Image.fromarray(np_style_image), (w, h))
+ pil_color_image = None if np_color_image is None else pad_image(Image.fromarray(np_color_image), (w, h))
+
+ input_images = [pil_layout_image, pil_style_image, pil_color_image, pil_fg_image]
+ input_texts = ['Layout', 'Style', 'Color', 'Subject']
+ input_compose_image = compose_image(input_images, input_texts, (w, h), nrow=2, ncol=2)
+ input_compose_image = input_compose_image.resize((w, h), Image.BICUBIC)
+ output_compose_image = compose_image([input_compose_image, pil_res_image], [None, None], (w, h), nrow=1,
+ ncol=2)
+ output_compose_image = add_prompt(output_compose_image, prompt, negative_prompt)
+
+ output_compose_image = np.array(output_compose_image)
+
+ return output_compose_image