Update app.py

app.py

@@ -19,19 +19,19 @@ import aoti
 
 MODEL_ID = "Wan-AI/Wan2.2-I2V-A14B-Diffusers"
 
-MAX_DIM = 640
+MAX_DIM = 832
 MIN_DIM = 480
 SQUARE_DIM = 640
 MULTIPLE_OF = 16
 
 MAX_SEED = np.iinfo(np.int32).max
 
-FIXED_FPS = 24
-MIN_FRAMES_MODEL = 24
-MAX_FRAMES_MODEL = 120
+FIXED_FPS = 16
+MIN_FRAMES_MODEL = 8
+MAX_FRAMES_MODEL = 80
 
 MIN_DURATION = round(MIN_FRAMES_MODEL/FIXED_FPS,1)
-MAX_DURATION = 5
+MAX_DURATION = round(MAX_FRAMES_MODEL/FIXED_FPS,1)
 
 
 pipe = WanImageToVideoPipeline.from_pretrained(MODEL_ID,
@@ -50,14 +50,14 @@ pipe = WanImageToVideoPipeline.from_pretrained(MODEL_ID,
 
 pipe.load_lora_weights(
     "Kijai/WanVideo_comfy", 
-    weight_name="Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank256_bf16.safetensors", 
+    weight_name="Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank128_bf16.safetensors", 
     adapter_name="lightx2v"
 )
 kwargs_lora = {}
 kwargs_lora["load_into_transformer_2"] = True
 pipe.load_lora_weights(
     "Kijai/WanVideo_comfy", 
-    weight_name="Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank256_bf16.safetensors", 
+    weight_name="Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank128_bf16.safetensors", 
     adapter_name="lightx2v_2", **kwargs_lora
 )
 pipe.set_adapters(["lightx2v", "lightx2v_2"], adapter_weights=[1., 1.])
@@ -142,7 +142,7 @@ def get_duration(
     randomize_seed,
     progress,
 ):
-    BASE_FRAMES_HEIGHT_WIDTH = 120 * 640 * 480
+    BASE_FRAMES_HEIGHT_WIDTH = 81 * 832 * 624
     BASE_STEP_DURATION = 10
     
     width, height = resize_image(input_image).size