Added product text box

app.py

@@ -219,11 +219,11 @@ def draw_box(box: torch.Tensor, draw: ImageDraw.Draw, label: Optional[str]) -> N
         draw.text((box[0], box[1]), str(label), fill="white")
 
 
-def run_grounded_sam(input_image):
+def run_grounded_sam(input_image, product):
     """Main function to run GroundingDINO and SAM-HQ"""
     # Create output directory
     os.makedirs(OUTPUT_DIR, exist_ok=True)
-    text_prompt = 'car'
+    text_prompt = product
     task_type = 'text'
     box_threshold = 0.3
     text_threshold = 0.25
@@ -533,7 +533,7 @@ def generate_ai_bg(input_img, prompt):
 
     return relight_img
 
-def blend_details(input_image, relit_image, masked_image, scaling_factor=1):
+def blend_details(input_image, relit_image, masked_image, product, scaling_factor=1):
 
     # input_image = resize_image(input_image)
 
@@ -616,9 +616,9 @@ def generate_image(input_image_path, prompt):
 
     ai_gen_image = generate_ai_bg(resized_input_img, prompt)
 
-    mask_input_image = run_grounded_sam(resized_input_img)
+    mask_input_image = run_grounded_sam(resized_input_img, product)
 
-    final_image = blend_details(resized_input_img, ai_gen_image, mask_input_image)
+    final_image = blend_details(resized_input_img, ai_gen_image, mask_input_image, product)
 
     return final_image
 
@@ -632,7 +632,7 @@ def create_ui():
         with gr.Row():
             with gr.Column():
                 input_image_path = gr.Image(type="filepath", label="image")
-                # ai_image = gr.Image(type="pil", label="image")
+                product = gr.Textbox(label="Product", placeholder="Enter what your product is here...")
                 prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
                 run_button = gr.Button(value='Run')
 
@@ -644,7 +644,7 @@ def create_ui():
             fn=generate_image, 
             inputs=[
                 input_image_path,
-                # ai_image,
+                product,
                 prompt
             ], 
             outputs=[output_image]