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Update app.py
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app.py
CHANGED
@@ -6,9 +6,9 @@ hf_token = os.environ.get("HF_TKN")
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from style_template import styles
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STYLE_NAMES = list(styles.keys())
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DEFAULT_STYLE_NAME = "
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def get_instantID(portrait_in, condition_pose, prompt):
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client = Client("https://fffiloni-instantid.hf.space/", hf_token=hf_token)
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negative_prompt = "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green"
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result = client.predict(
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@@ -16,7 +16,7 @@ def get_instantID(portrait_in, condition_pose, prompt):
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condition_pose, # filepath in 'Upload a reference pose image (optional)' Image component
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prompt, # str in 'Prompt' Textbox component
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negative_prompt, # str in 'Negative Prompt' Textbox component
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True, # bool in 'Enhance non-face region' Checkbox component
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20, # float (numeric value between 20 and 100) in 'Number of sample steps' Slider component
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0.8, # float (numeric value between 0 and 1.5) in 'IdentityNet strength (for fedility)' Slider component
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@@ -54,7 +54,7 @@ def get_video_svd(image_in):
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print(result)
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return result[0]["video"]
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def infer(image_in, camera_shot, conditional_pose, prompt, chosen_model):
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if camera_shot == "custom":
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if conditional_pose != None:
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conditional_pose = conditional_pose
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@@ -74,7 +74,7 @@ def infer(image_in, camera_shot, conditional_pose, prompt, chosen_model):
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elif camera_shot == "full shot":
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conditional_pose = "camera_shots/full_shot.jpeg"
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iid_img = get_instantID(image_in, conditional_pose, prompt)
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if chosen_model == "i2vgen-xl" :
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video_res = get_video_i2vgen(iid_img, prompt)
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@@ -134,6 +134,7 @@ with gr.Blocks(css=css) as demo:
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camera_shot,
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condition_shot,
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prompt,
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chosen_model
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],
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outputs = [
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from style_template import styles
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STYLE_NAMES = list(styles.keys())
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DEFAULT_STYLE_NAME = "(No Style)"
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def get_instantID(portrait_in, condition_pose, prompt, style):
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client = Client("https://fffiloni-instantid.hf.space/", hf_token=hf_token)
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negative_prompt = "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green"
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result = client.predict(
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condition_pose, # filepath in 'Upload a reference pose image (optional)' Image component
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prompt, # str in 'Prompt' Textbox component
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negative_prompt, # str in 'Negative Prompt' Textbox component
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style, # Literal['(No style)', 'Watercolor', 'Film Noir', 'Neon', 'Jungle', 'Mars', 'Vibrant Color', 'Snow', 'Line art'] in 'Style template' Dropdown component
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True, # bool in 'Enhance non-face region' Checkbox component
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20, # float (numeric value between 20 and 100) in 'Number of sample steps' Slider component
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0.8, # float (numeric value between 0 and 1.5) in 'IdentityNet strength (for fedility)' Slider component
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print(result)
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return result[0]["video"]
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def infer(image_in, camera_shot, conditional_pose, prompt, style, chosen_model):
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if camera_shot == "custom":
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if conditional_pose != None:
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conditional_pose = conditional_pose
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elif camera_shot == "full shot":
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conditional_pose = "camera_shots/full_shot.jpeg"
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iid_img = get_instantID(image_in, conditional_pose, prompt, style)
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if chosen_model == "i2vgen-xl" :
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video_res = get_video_i2vgen(iid_img, prompt)
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camera_shot,
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condition_shot,
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prompt,
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style,
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chosen_model
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],
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outputs = [
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