remove examples
Browse files
app.py
CHANGED
@@ -41,221 +41,6 @@ def generate_image(text, img1, img2, img3, height, width, guidance_scale, img_gu
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img = output[0]
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return img
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def get_example():
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case = [
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[
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"A curly-haired man in a red shirt is drinking tea.",
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None,
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None,
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None,
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1024,
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1024,
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2.5,
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1.6,
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0,
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1024,
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False,
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False,
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],
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[
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"The woman in <img><|image_1|></img> waves her hand happily in the crowd",
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"./imgs/test_cases/zhang.png",
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None,
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None,
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1024,
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1024,
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2.5,
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1.9,
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128,
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1024,
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False,
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False,
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],
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[
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"A man in a black shirt is reading a book. The man is the right man in <img><|image_1|></img>.",
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"./imgs/test_cases/two_man.jpg",
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None,
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None,
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1024,
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1024,
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2.5,
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1.6,
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0,
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1024,
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False,
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False,
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],
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[
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"Two woman are raising fried chicken legs in a bar. A woman is <img><|image_1|></img>. Another woman is <img><|image_2|></img>.",
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"./imgs/test_cases/mckenna.jpg",
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"./imgs/test_cases/Amanda.jpg",
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None,
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1024,
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1024,
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2.5,
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1.8,
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65,
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1024,
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False,
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False,
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],
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[
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"A man and a short-haired woman with a wrinkled face are standing in front of a bookshelf in a library. The man is the man in the middle of <img><|image_1|></img>, and the woman is oldest woman in <img><|image_2|></img>",
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"./imgs/test_cases/1.jpg",
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"./imgs/test_cases/2.jpg",
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None,
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1024,
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1024,
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2.5,
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1.6,
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60,
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1024,
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False,
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False,
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],
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[
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"A man and a woman are sitting at a classroom desk. The man is the man with yellow hair in <img><|image_1|></img>. The woman is the woman on the left of <img><|image_2|></img>",
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"./imgs/test_cases/3.jpg",
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"./imgs/test_cases/4.jpg",
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None,
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1024,
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1024,
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2.5,
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1.8,
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66,
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1024,
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False,
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False,
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],
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[
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"The flower <img><|image_1|></img> is placed in the vase which is in the middle of <img><|image_2|></img> on a wooden table of a living room",
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"./imgs/test_cases/rose.jpg",
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"./imgs/test_cases/vase.jpg",
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None,
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1024,
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1024,
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2.5,
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1.6,
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0,
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1024,
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False,
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False,
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],
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[
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"<img><|image_1|><img>\n Remove the woman's earrings. Replace the mug with a clear glass filled with sparkling iced cola.",
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"./imgs/demo_cases/t2i_woman_with_book.png",
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None,
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None,
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None,
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None,
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2.5,
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1.6,
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222,
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1024,
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False,
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True,
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],
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[
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"Detect the skeleton of human in this image: <img><|image_1|></img>.",
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"./imgs/test_cases/control.jpg",
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None,
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None,
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1024,
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1024,
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2.0,
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1.6,
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0,
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1024,
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False,
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True,
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],
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[
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"Generate a new photo using the following picture and text as conditions: <img><|image_1|><img>\n A young boy is sitting on a sofa in the library, holding a book. His hair is neatly combed, and a faint smile plays on his lips, with a few freckles scattered across his cheeks. The library is quiet, with rows of shelves filled with books stretching out behind him.",
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"./imgs/demo_cases/skeletal.png",
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None,
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None,
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1024,
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1024,
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2,
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1.6,
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999,
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1024,
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False,
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True,
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],
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[
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"Following the pose of this image <img><|image_1|><img>, generate a new photo: A young boy is sitting on a sofa in the library, holding a book. His hair is neatly combed, and a faint smile plays on his lips, with a few freckles scattered across his cheeks. The library is quiet, with rows of shelves filled with books stretching out behind him.",
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"./imgs/demo_cases/edit.png",
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None,
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None,
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1024,
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1024,
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2.0,
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1.6,
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123,
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1024,
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False,
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True,
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],
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[
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"Following the depth mapping of this image <img><|image_1|><img>, generate a new photo: A young girl is sitting on a sofa in the library, holding a book. His hair is neatly combed, and a faint smile plays on his lips, with a few freckles scattered across his cheeks. The library is quiet, with rows of shelves filled with books stretching out behind him.",
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"./imgs/demo_cases/edit.png",
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None,
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None,
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1024,
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1024,
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2.0,
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1.6,
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1,
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1024,
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False,
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True,
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],
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[
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"<img><|image_1|><\/img> What item can be used to see the current time? Please highlight it in blue.",
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"./imgs/test_cases/watch.jpg",
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None,
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None,
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1024,
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1024,
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2.5,
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1.6,
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666,
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1024,
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False,
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True,
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],
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[
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"According to the following examples, generate an output for the input.\nInput: <img><|image_1|></img>\nOutput: <img><|image_2|></img>\n\nInput: <img><|image_3|></img>\nOutput: ",
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"./imgs/test_cases/icl1.jpg",
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"./imgs/test_cases/icl2.jpg",
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"./imgs/test_cases/icl3.jpg",
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224,
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224,
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2.5,
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1.6,
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1,
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768,
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False,
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False,
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],
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]
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return case
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def run_for_examples(text, img1, img2, img3, height, width, guidance_scale, img_guidance_scale, seed, max_input_image_size, randomize_seed, use_input_image_size_as_output):
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# 在函数内部设置默认值
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inference_steps = 50
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separate_cfg_infer = True
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offload_model = False
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return generate_image(
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text, img1, img2, img3, height, width, guidance_scale, img_guidance_scale,
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inference_steps, seed, separate_cfg_infer, offload_model,
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use_input_image_size_as_output, max_input_image_size, randomize_seed
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)
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description = """
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OmniGen is a unified image generation model that you can use to perform various tasks, including but not limited to text-to-image generation, subject-driven generation, Identity-Preserving Generation, and image-conditioned generation.
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For multi-modal to image generation, you should pass a string as `prompt`, and a list of image paths as `input_images`. The placeholder in the prompt should be in the format of `<img><|image_*|></img>` (for the first image, the placeholder is <img><|image_1|></img>. for the second image, the the placeholder is <img><|image_2|></img>).
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@@ -379,26 +164,6 @@ with gr.Blocks() as demo:
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outputs=output_image,
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)
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gr.Examples(
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examples=get_example(),
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fn=run_for_examples,
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inputs=[
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prompt_input,
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image_input_1,
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image_input_2,
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image_input_3,
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height_input,
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width_input,
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guidance_scale_input,
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img_guidance_scale_input,
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seed_input,
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max_input_image_size,
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randomize_seed,
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use_input_image_size_as_output,
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],
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outputs=output_image,
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)
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gr.Markdown(article)
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# launch
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img = output[0]
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return img
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description = """
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OmniGen is a unified image generation model that you can use to perform various tasks, including but not limited to text-to-image generation, subject-driven generation, Identity-Preserving Generation, and image-conditioned generation.
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For multi-modal to image generation, you should pass a string as `prompt`, and a list of image paths as `input_images`. The placeholder in the prompt should be in the format of `<img><|image_*|></img>` (for the first image, the placeholder is <img><|image_1|></img>. for the second image, the the placeholder is <img><|image_2|></img>).
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outputs=output_image,
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)
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gr.Markdown(article)
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# launch
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