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api/index.py

@@ -101,36 +101,36 @@ def image_classifier(moodboard, starter_image, image_strength, prompt):
         raise gr.Error(f"Please upload a moodboard to control image generation style")
         
     # Call Stable Diffusion API with the response from OpenAI
-    # input = {
-    #     "width": 768,
-    #     "height": 768,
-    #     "prompt": "high quality render of " + prompt + ", " + openai_response[12:],
-    #     "negative_prompt": "worst quality, low quality, illustration, 2d, painting, cartoons, sketch",
-    #     "refine": "expert_ensemble_refiner",
-    #     "image": "data:image/jpeg;base64," + starter_image_base64, 
-    #     "apply_watermark": False,
-    #     "num_inference_steps": 25,
-    #     "prompt_strength": 1-image_strength,
-    #     "num_outputs": 3
-    # }
+    input = {
+        "width": 768,
+        "height": 768,
+        "prompt": "high quality render of " + prompt + ", " + openai_response[12:],
+        "negative_prompt": "worst quality, low quality, illustration, 2d, painting, cartoons, sketch",
+        "refine": "expert_ensemble_refiner",
+        "image": "data:image/jpeg;base64," + starter_image_base64, 
+        "apply_watermark": False,
+        "num_inference_steps": 25,
+        "prompt_strength": 1-image_strength,
+        "num_outputs": 3
+    }
     
-    # output = replicate.run(
-    #     "stability-ai/sdxl:7762fd07cf82c948538e41f63f77d685e02b063e37e496e96eefd46c929f9bdc",
-    #     input=input
-    # )
+    output = replicate.run(
+        "stability-ai/sdxl:7762fd07cf82c948538e41f63f77d685e02b063e37e496e96eefd46c929f9bdc",
+        input=input
+    )
     
-    # images = []
-    # for i in range(min(len(output), 3)):
-    #     image_url = output[i]
-    #     response = requests.get(image_url)
-    #     images.append(Image.open(io.BytesIO(response.content)))
+    images = []
+    for i in range(min(len(output), 3)):
+        image_url = output[i]
+        response = requests.get(image_url)
+        images.append(Image.open(io.BytesIO(response.content)))
     
-    # # Add empty images if fewer than 3 were returned
-    # while len(images) < 3:
-    #     images.append(Image.new('RGB', (768, 768), 'gray'))
+    # Add empty images if fewer than 3 were returned
+    while len(images) < 3:
+        images.append(Image.new('RGB', (768, 768), 'gray'))
 
-    # return images
+    return images
 
-header = "Set up APIs on HuggingFace or use free at https://app.idai.tools/"
+header = "Set up APIs on HuggingFace or use free at https://app.idai.tools/ (https://app.idai.tools/interface/moodboard_controlled)"
 demo = gr.Interface(fn=image_classifier, inputs=["image", "image", gr.Slider(0, 1, step=0.05, value=0.2, label="Image Strength"), "text"], outputs=["image", "image", "image"], title=header)
 demo.launch(share=False)