Update app.py

app.py

@@ -1,31 +1,48 @@
 import gradio as gr
 from gradio_client import Client
 import os 
+import random
 
 hf_token = os.environ.get("HF_TKN")
 
+# global variable
+MAX_SEED = np.iinfo(np.int32).max
 from style_template import styles
 STYLE_NAMES = list(styles.keys())
 DEFAULT_STYLE_NAME = "(No style)"
 
+def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    return seed
+
 def get_instantID(portrait_in, condition_pose, prompt, style):
-    client = Client("https://fffiloni-instantid.hf.space/", hf_token=hf_token)
+    
     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, monochrome, gun, weapon"
+    seed = random.randint(0, MAX_SEED)
+    
+    client = Client("https://instantx-instantid.hf.space/")
     result = client.predict(
 		portrait_in,	# filepath  in 'Upload a photo of your face' Image component
-		condition_pose,	# filepath  in 'Upload a reference pose image (optional)' Image component
-	    prompt,	# str  in 'Prompt' Textbox component
+		condition_pose,	# filepath  in 'Upload a reference pose image (Optional)' Image component
+		prompt,	# str  in 'Prompt' Textbox component
 		negative_prompt,	# str  in 'Negative Prompt' Textbox component
-		style,	# Literal['(No style)', 'Watercolor', 'Film Noir', 'Neon', 'Jungle', 'Mars', 'Vibrant Color', 'Snow', 'Line art']  in 'Style template' Dropdown component
-		True,	# bool  in 'Enhance non-face region' Checkbox component
-		20,	# float (numeric value between 20 and 100) in 'Number of sample steps' Slider component
-		0.8,	# float (numeric value between 0 and 1.5) in 'IdentityNet strength (for fedility)' Slider component
+		style,	# Literal['(No style)', 'Spring Festival', 'Watercolor', 'Film Noir', 'Neon', 'Jungle', 'Mars', 'Vibrant Color', 'Snow', 'Line art']  in 'Style template' Dropdown component
+		20,	# float (numeric value between 1 and 100) in 'Number of sample steps' Slider component
+		0.8,	# float (numeric value between 0 and 1.5) in 'IdentityNet strength (for fidelity)' Slider component
 		0.8,	# float (numeric value between 0 and 1.5) in 'Image adapter strength (for detail)' Slider component
-		5,	# float (numeric value between 0.1 and 10.0) in 'Guidance scale' Slider component
+		0.4,	# float (numeric value between 0 and 1.5) in 'Pose strength' Slider component
+		0.4,	# float (numeric value between 0 and 1.5) in 'Canny strength' Slider component
+		0.4,	# float (numeric value between 0 and 1.5) in 'Depth strength' Slider component
+		["pose"],	# List[Literal['pose', 'canny', 'depth']]  in 'Controlnet' Checkboxgroup component
+		5,	# float (numeric value between 0.1 and 20.0) in 'Guidance scale' Slider component
 		0,	# float (numeric value between 0 and 2147483647) in 'Seed' Slider component
-        True,	# bool  in 'Randomize seed' Checkbox component
+		"EulerDiscreteScheduler",	# Literal['DEISMultistepScheduler', 'HeunDiscreteScheduler', 'EulerDiscreteScheduler', 'DPMSolverMultistepScheduler', 'DPMSolverMultistepScheduler-Karras', 'DPMSolverMultistepScheduler-Karras-SDE']  in 'Schedulers' Dropdown component
+		True,	# bool  in 'Enable Fast Inference with LCM' Checkbox component
+		True,	# bool  in 'Enhance non-face region' Checkbox component
 		api_name="/generate_image"
     )
+    
     print(result)
     return result[0]
 
@@ -42,7 +59,7 @@ def get_video_i2vgen(image_in, prompt):
 def get_video_svd(image_in):
     from gradio_client import Client
 
-    client = Client("https://multimodalart-stable-video-diffusion.hf.space/--replicas/ej45m/")
+    client = Client("https://multimodalart-stable-video-diffusion.hf.space/")
     result = client.predict(
 		image_in,	# filepath  in 'Upload your image' Image component
 		0,	# float (numeric value between 0 and 9223372036854775807) in 'Seed' Slider component