Update app.py

app.py

@@ -17,6 +17,7 @@ from diffusers import EulerDiscreteScheduler
 from PIL import Image, ImageDraw, ImageFont
 import os
 
+
 device = "cuda"
 ckpt_dir = snapshot_download(repo_id="Kwai-Kolors/Kolors")
 ckpt_dir_canny = snapshot_download(repo_id="Kwai-Kolors/Kolors-ControlNet-Canny")
@@ -111,8 +112,9 @@ def text_to_image(text, size=72, position="middle-center"):
 
     return image
 
+
 @spaces.GPU
-def infer_canny(prompt, 
+def infer_canny(prompt, text_for_image, 
           negative_prompt = "nsfw, facial shadows, low resolution, jpeg artifacts, blurry, bad quality, dark face, neon lights", 
           seed = 397886929, 
           randomize_seed = False,
@@ -130,7 +132,7 @@ def infer_canny(prompt,
     generator = torch.Generator().manual_seed(seed)
     
     # Generate text image
-    init_image = text_to_image(prompt)
+    init_image = text_to_image(text_for_image)
     init_image = resize_image(init_image, MAX_IMAGE_SIZE)
     
     pipe = pipe_canny.to("cuda")
@@ -165,6 +167,12 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as Kolors:
                     placeholder="Enter your prompt",
                     lines=2
                 )
+            with gr.Row():
+                text_for_image = gr.Textbox(
+                    label="Text for Image Generation",
+                    placeholder="Enter text to be converted into an image",
+                    lines=3
+                )
             with gr.Accordion("Advanced Settings", open=False):
                 negative_prompt = gr.Textbox(
                     label="Negative prompt",
@@ -227,8 +235,8 @@ with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as Kolors:
 
     canny_button.click(
         fn = infer_canny,
-        inputs = [prompt, negative_prompt, seed, randomize_seed, guidance_scale, num_inference_steps, controlnet_conditioning_scale, control_guidance_end, strength],
+        inputs = [prompt, text_for_image, negative_prompt, seed, randomize_seed, guidance_scale, num_inference_steps, controlnet_conditioning_scale, control_guidance_end, strength],
         outputs = [result, seed_used]
     )
 
-Kolors.queue().launch(debug=True)  
+Kolors.queue().launch(debug=True)