change parameters for more realism

inference.py

@@ -186,14 +186,10 @@ def find_similar_ikea_products(image_input, index, metadata_df, top_k=5, process
     return results
 
 
-def generate_image(prompt, control_image, guidance_scale, output_quality, negative_prompt, control_strength):
+def generate_image(prompt, control_image, guidance_scale, output_quality, negative_prompt, control_strength, image_to_image_strength, control_type):
     logging.info("\nGenerating image with Stable Diffusion...")
     logging.info(f"Prompt: {prompt}")
-    guidance_scale = 2.5
-    output_quality = 100
-    negative_prompt = "low quality, ugly, distorted, artefacts"
-    control_strength = 0.45
-    # Modify the input handling to work with file paths
+
     if isinstance(control_image, str):
         image = open(control_image, "rb")
     else:
@@ -205,7 +201,9 @@ def generate_image(prompt, control_image, guidance_scale, output_quality, negati
         "guidance_scale": guidance_scale,
         "output_quality": output_quality,
         "negative_prompt": negative_prompt,
-        "control_strength": control_strength
+        "control_strength": control_strength,
+        "image_to_image_strength": image_to_image_strength,
+        "control_type": control_type
     }
 
     logging.info("Running image generation model...")
@@ -222,7 +220,6 @@ def generate_image(prompt, control_image, guidance_scale, output_quality, negati
 
 # step 2
 
-
 def analyze_image(image_path):  
     logging.info(f"\nAnalyzing image with GPT-4V: {image_path}")
 
@@ -327,7 +324,9 @@ def main(prompt, control_image, index, metadata_df):
         guidance_scale=2.5,
         output_quality=100,
         negative_prompt="low quality, ugly, distorted, artefacts",
-        control_strength=0.95
+        control_strength=0.5,
+        image_to_image_strength=0.1,
+        control_type="canny"
     )
     results['generated_images'] = generated_images
     results['generated_image_path'] = "output_0.jpg"