added resize method, now large images are working

app.py

@@ -8,6 +8,8 @@ from PIL import Image
 from diffusers import FlaxStableDiffusionControlNetPipeline, FlaxControlNetModel
 import cv2
 
+
+
 title = "ControlNet for Cartoon-ifying"
 description = "This is a demo on ControlNet for changing images of people into cartoons of different styles."
 examples = [["./simpsons_human_1.jpg", "turn into a simpsons character", "./simpsons_animated_1.jpg"]]
@@ -30,17 +32,31 @@ pipe, params = FlaxStableDiffusionControlNetPipeline.from_pretrained(
     "runwayml/stable-diffusion-v1-5", controlnet=controlnet, revision="flax", dtype=jnp.bfloat16
 )
 
+def resize_image(im, max_size):
+    im_np = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
+
+    height, width = im_np.shape[:2]
+
+    scale_factor = max_size / max(height, width)
+
+    resized_np = cv2.resize(im_np, (int(width * scale_factor), int(height * scale_factor)))
+
+    resized_im = Image.fromarray(resized_np)
+
+    return resized_im
+
 def create_key(seed=0):
     return jax.random.PRNGKey(seed)
 
 def infer(prompts, image):
     params["controlnet"] = controlnet_params
     
+    image = resize_image(image, 500)
     num_samples = 1 #jax.device_count()
     rng = create_key(0)
     rng = jax.random.split(rng, jax.device_count())
-    im = image
-    image = Image.fromarray(im)
+    #im = image
+    #image = Image.fromarray(im)
     
     prompt_ids = pipe.prepare_text_inputs([prompts] * num_samples)
     processed_image = pipe.prepare_image_inputs([image] * num_samples)