Update app.py

app.py

@@ -285,14 +285,12 @@ def generate_30(
     ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
     seed = int(randomize_seed_fn(seed, randomize_seed))
     generator = torch.Generator(device='cuda').manual_seed(seed)
-    if latent_file.any():  # Check if a latent file is provided
-        #sd_image_a = torch.load(latent_file.name)  # Load the latent
-        #sd_image_a = latent_file #Image.open(latent_file)
+    if latent_file is not None:  # Check if a latent file is provided
         if not isinstance(latent_file, Image.Image):
-            image = Image.fromarray(latent_file) 
+            image = Image.fromarray(latent_file)
         image = image.resize((width, height))  # Example resize, adjust as needed
         image = image.convert("RGB")  # Ensure it's a 3-channel image
-        image = np.array(image)  
+        image = np.array(image)
         sd_image_a = torch.from_numpy(image).permute(2, 0, 1) / 127.5 - 1.0  # Normalize
         timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
         filename= f'rv_IP_{timestamp}.txt'
@@ -345,14 +343,12 @@ def generate_60(
     ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
     seed = int(randomize_seed_fn(seed, randomize_seed))
     generator = torch.Generator(device='cuda').manual_seed(seed)
-    if latent_file.any():  # Check if a latent file is provided
-        #sd_image_a = torch.load(latent_file.name)  # Load the latent
-        #sd_image_a = latent_file #Image.open(latent_file)
+    if latent_file is not None:  # Check if a latent file is provided
         if not isinstance(latent_file, Image.Image):
-            image = Image.fromarray(latent_file) 
+            image = Image.fromarray(latent_file)
         image = image.resize((width, height))  # Example resize, adjust as needed
         image = image.convert("RGB")  # Ensure it's a 3-channel image
-        image = np.array(image)  
+        image = np.array(image)
         sd_image_a = torch.from_numpy(image).permute(2, 0, 1) / 127.5 - 1.0  # Normalize
         timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
         filename= f'rv_IP_{timestamp}.txt'
@@ -405,14 +401,12 @@ def generate_90(
     ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
     seed = int(randomize_seed_fn(seed, randomize_seed))
     generator = torch.Generator(device='cuda').manual_seed(seed)
-    if latent_file.any():  # Check if a latent file is provided
-        #sd_image_a = torch.load(latent_file.name)  # Load the latent
-        #sd_image_a = latent_file #Image.open(latent_file)
+    if latent_file is not None:  # Check if a latent file is provided
         if not isinstance(latent_file, Image.Image):
-            image = Image.fromarray(latent_file) 
+            image = Image.fromarray(latent_file)
         image = image.resize((width, height))  # Example resize, adjust as needed
         image = image.convert("RGB")  # Ensure it's a 3-channel image
-        image = np.array(image)  
+        image = np.array(image)
         sd_image_a = torch.from_numpy(image).permute(2, 0, 1) / 127.5 - 1.0  # Normalize
         timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
         filename= f'rv_IP_{timestamp}.txt'