Adding API & Gradio

ComfyUI_API.py

@@ -0,0 +1,298 @@
+import json
+from urllib import request, parse
+import gradio as gr
+import random
+import os 
+import matplotlib.pyplot as plt
+import matplotlib.image as mpimg
+from PIL import Image as PILImage
+
+prompt_text = """
+{
+  "10": {
+    "inputs": {
+      "ckpt_name": "DreamShaper_8_pruned.safetensors",
+      "vae_name": "vae-ft-mse-840000-ema-pruned.ckpt",
+      "clip_skip": -2,
+      "lora_name": "None",
+      "lora_model_strength": 1,
+      "lora_clip_strength": 1,
+      "positive": "In the style of Grand Theft Auto, loading screens, (palm trees), GTA style artwork, highly detailed, urban scene with numerous palm trees, neon lights, and graffiti, trending on ArtStation, preserving the individual's race, color and hair.",
+      "negative": "(worst quality, low quality = 1.3)",
+      "token_normalization": "none",
+      "weight_interpretation": "comfy",
+      "empty_latent_width": [
+        "65",
+        0
+      ],
+      "empty_latent_height": [
+        "65",
+        1
+      ],
+      "batch_size": 1,
+      "cnet_stack": [
+        "11",
+        0
+      ]
+    },
+    "class_type": "Efficient Loader",
+    "_meta": {
+      "title": "Efficient Loader"
+    }
+  },
+  "11": {
+    "inputs": {
+      "switch_1": "On",
+      "controlnet_1": "control_v11p_sd15_lineart_fp16.safetensors",
+      "controlnet_strength_1": 0.7000000000000001,
+      "start_percent_1": 0,
+      "end_percent_1": 1,
+      "switch_2": "On",
+      "controlnet_2": "control_v11p_sd15_openpose_fp16.safetensors",
+      "controlnet_strength_2": 1,
+      "start_percent_2": 0,
+      "end_percent_2": 1,
+      "switch_3": "Off",
+      "controlnet_3": "None",
+      "controlnet_strength_3": 0.99,
+      "start_percent_3": 0,
+      "end_percent_3": 1,
+      "image_1": [
+        "107",
+        0
+      ],
+      "image_2": [
+        "109",
+        0
+      ]
+    },
+    "class_type": "CR Multi-ControlNet Stack",
+    "_meta": {
+      "title": "🕹️ CR Multi-ControlNet Stack"
+    }
+  },
+  "12": {
+    "inputs": {
+      "low_threshold": 100,
+      "high_threshold": 200,
+      "resolution": 2048,
+      "image": [
+        "14",
+        0
+      ]
+    },
+    "class_type": "CannyEdgePreprocessor",
+    "_meta": {
+      "title": "Canny Edge"
+    }
+  },
+  "13": {
+    "inputs": {
+      "images": [
+        "12",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "14": {
+    "inputs": {
+      "image": "IMG_7593_2 (10).jpg",
+      "upload": "image"
+    },
+    "class_type": "LoadImage",
+    "_meta": {
+      "title": "Load Image"
+    }
+  },
+  "64": {
+    "inputs": {
+      "seed": 4091745839,
+      "steps": 10,
+      "cfg": 4,
+      "sampler_name": "dpm_fast",
+      "scheduler": "karras",
+      "denoise": 1,
+      "preview_method": "auto",
+      "vae_decode": "true",
+      "model": [
+        "10",
+        0
+      ],
+      "positive": [
+        "10",
+        1
+      ],
+      "negative": [
+        "10",
+        2
+      ],
+      "latent_image": [
+        "10",
+        3
+      ],
+      "optional_vae": [
+        "10",
+        4
+      ],
+      "script": [
+        "101",
+        0
+      ]
+    },
+    "class_type": "KSampler (Efficient)",
+    "_meta": {
+      "title": "KSampler (Efficient)"
+    }
+  },
+  "65": {
+    "inputs": {
+      "width": 512,
+      "height": 512,
+      "aspect_ratio": "SD1.5 - 2:3 portrait 512x768",
+      "swap_dimensions": "Off",
+      "upscale_factor": 1,
+      "prescale_factor": 1,
+      "batch_size": 1
+    },
+    "class_type": "CR Aspect Ratio",
+    "_meta": {
+      "title": "🔳 CR Aspect Ratio"
+    }
+  },
+  "99": {
+    "inputs": {
+      "filename_prefix": "image",
+      "images": [
+        "64",
+        5
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "Save Image"
+    }
+  },
+  "101": {
+    "inputs": {
+      "grid_spacing": 0,
+      "XY_flip": "False",
+      "Y_label_orientation": "Horizontal",
+      "cache_models": "True",
+      "ksampler_output_image": "Images",
+      "X": [
+        "102",
+        0
+      ]
+    },
+    "class_type": "XY Plot",
+    "_meta": {
+      "title": "XY Plot"
+    }
+  },
+  "102": {
+    "inputs": {
+      "batch_count": 1,
+      "first_cfg": 4,
+      "last_cfg": 4
+    },
+    "class_type": "XY Input: CFG Scale",
+    "_meta": {
+      "title": "XY Input: CFG Scale"
+    }
+  },
+  "107": {
+    "inputs": {
+      "mode": "anime",
+      "image": [
+        "14",
+        0
+      ]
+    },
+    "class_type": "Lineart_Detector_Preprocessor",
+    "_meta": {
+      "title": "Lineart_Detector_Preprocessor"
+    }
+  },
+  "108": {
+    "inputs": {
+      "images": [
+        "107",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  },
+  "109": {
+    "inputs": {
+      "include_face": true,
+      "include_hand": true,
+      "include_body": true,
+      "image": [
+        "14",
+        0
+      ]
+    },
+    "class_type": "Openpose_Detector_Preprocessor",
+    "_meta": {
+      "title": "Openpose_Detector_Preprocessor"
+    }
+  },
+  "110": {
+    "inputs": {
+      "images": [
+        "109",
+        0
+      ]
+    },
+    "class_type": "PreviewImage",
+    "_meta": {
+      "title": "Preview Image"
+    }
+  }
+}
+"""
+
+def queue_prompt(prompt):
+    p = {"prompt": prompt}
+    data = json.dumps(p).encode('utf-8')
+    req = request.Request("http://127.0.0.1:8188/prompt", data=data)
+    request.urlopen(req)
+
+def generate_images(positive_prompt, negative_prompt, seed, image_path):
+    prompt = json.loads(prompt_text)
+    # Set the text prompt for our positive CLIPTextEncode
+    prompt["10"]["inputs"]["positive"] = positive_prompt
+    prompt["10"]["inputs"]["negative"] = negative_prompt
+    prompt["14"]["inputs"]["image"] = image_path
+    
+    queue_prompt(prompt)
+    output_dir = "/Users/paresh/ComfyUI/output/"
+    current_count = 56
+    next_filename = f"image_{str(current_count + 1).zfill(5)}_.png"
+    output_image_path = os.path.join(output_dir, next_filename)
+    generated_image = PILImage.open(output_image_path)
+
+    return generated_image
+
+# Gradio Interface
+seed = gr.Number(value=43857297359, label="Seed")
+image = gr.Image(type="filepath", label="Upload Image")
+positive_prompt = gr.Textbox(lines=2, placeholder="Enter positive prompt")
+negative_prompt = gr.Textbox(lines=1, placeholder="Enter negative prompt")
+
+interface = gr.Interface(
+    fn=generate_images,
+    inputs=[positive_prompt, negative_prompt, seed, image],
+    outputs="text",
+    title="Image Generation with Custom Prompts",
+    description="Generate images in the style of GTA/Anime with customizable prompts with a image input.",
+)
+
+interface.launch()