Add files via upload

Render_config.yaml

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+fbx_model_path: "./tmp.obj"
+output_folder: './'
+# textures:
+#   back: "path/to/your/texture/back.png"
+#   front: "path/to/your/texture/front.png"
+#   left: "path/to/your/texture/left.png"
+sd_model_checkpoint: 'darkSushi25D25D_v40.safetensors'
+seg_node:
+  random_color: True
+depth_node:
+  map_value_node_offset: 0.5
+  map_value_node_size: 0.7
+camera:
+  view: ['back','front','left','right']
+  distance: 1.5
+  side_angle: 80
+resolution:
+  width: 1600
+  height: 1600
+textures: {
+    back: "./Sres_0.png",
+    front: "./Sres_1.png",
+    left: "./Sres_2.png"
+    # 'right': sides_image
+}
+inpaint_textures: {
+    back: "./Sres_0_brinting.png",
+    front: "./Sres_1_brinting.png",
+    left: "./Sres_inpainted_1.png",
+    right: "./Sres_inpainted_0.png"
+}
+project_order: ['back','front','left','right']

Sres.py

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+import base64
+import io
+import json
+import requests
+from PIL import Image
+
+def image_to_base64(image_path):
+    with Image.open(image_path) as img:
+        buffer = io.BytesIO()
+        img.save(buffer, format="PNG")
+        return base64.b64encode(buffer.getvalue()).decode()
+
+def base64_to_image(base64_data, output_path):
+    img_data = base64.b64decode(base64_data)
+    img = Image.open(io.BytesIO(img_data))
+    img.save(output_path, format="PNG")
+
+
+img1 = image_to_base64("resample_0.jpg")
+img2 = image_to_base64("resample_1.jpg")
+
+img_list = [img1,img2]
+url = "http://127.0.0.1:7860/sdapi/v1/extra-single-image"
+for i,img in enumerate(img_list):
+    data = {
+    "resize_mode": 1,
+    "show_extras_results": False,
+    "gfpgan_visibility": 0,
+    "codeformer_visibility": 0,
+    "codeformer_weight": 0,
+    # "upscaling_resize": 0,#By how much to upscale the image, only used when resize_mode=0.
+    "upscaling_resize_w": 6400,
+    "upscaling_resize_h": 6400,
+        "upscaling_crop": False,
+        "upscaler_1": "4x-UltraSharp",
+        # "upscaler_2": "4x-UltraSharp",
+        #"extras_upscaler_2_visibility": 0.5,
+        "upscale_first": False,
+    "image": img
+    }
+    # data = {
+    # "resize_mode": 0,
+    # "show_extras_results": False,
+    # "gfpgan_visibility": 0,
+    # "codeformer_visibility": 0,
+    # "codeformer_weight": 0,
+    # "upscaling_resize": 1,
+    # "upscaling_resize_w": 4096,
+    # "upscaling_resize_h": 4096,
+    # "upscaling_crop": False,
+    # "upscaler_1": "SwinIR_4x",
+    # "upscaler_2": "R-ESRGAN 4x+ Anime6B",
+    # "extras_upscaler_2_visibility": 0.5,
+    # "upscale_first": False,
+    # "imageList": [
+    # {
+    #     "data": img1,
+    #     "name": "C:\\Users\\y\\code\\ppainter\\restored_image_1.jpg"
+    # }
+    # ]
+    # }
+
+    headers = {"Content-Type": "application/json"}
+
+    response = requests.post(url, data=json.dumps(data), headers=headers)
+
+    if response.status_code == 200:
+        print("Request was successful")
+        response_data = response.json()
+        output_image_path = "Sres_{}.png"
+        base64_to_image(response_data["image"], output_image_path.format(str(i)))
+        print(f"Saved output image to {output_image_path.format(str(i))}")
+    else:
+        print(f"Request failed with status code {response.status_code}")

Sres_inpaint.py

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+import base64
+import io
+import json
+import requests
+from PIL import Image
+
+def image_to_base64(image_path):
+    with Image.open(image_path) as img:
+        buffer = io.BytesIO()
+        img.save(buffer, format="PNG")
+        return base64.b64encode(buffer.getvalue()).decode()
+
+def base64_to_image(base64_data, output_path):
+    img_data = base64.b64decode(base64_data)
+    img = Image.open(io.BytesIO(img_data))
+    img.save(output_path, format="PNG")
+
+
+img1 = image_to_base64("inpainted_0.png")
+img2 = image_to_base64("inpainted_1.png")
+img_list = [img1,img2]
+url = "http://127.0.0.1:7860/sdapi/v1/extra-single-image"
+for i,img in enumerate(img_list):
+    data = {
+    "resize_mode": 1,
+    "show_extras_results": False,
+    "gfpgan_visibility": 0,
+    "codeformer_visibility": 0,
+    "codeformer_weight": 0,
+    # "upscaling_resize": 0,#By how much to upscale the image, only used when resize_mode=0.
+    "upscaling_resize_w": 6400,
+    "upscaling_resize_h": 6400,
+        "upscaling_crop": False,
+        "upscaler_1": "4x-UltraSharp",
+        # "upscaler_2": "4x-UltraSharp",
+        # "extras_upscaler_2_visibility": 0.5,
+        "upscale_first": False,
+    "image": img
+    }
+    # data = {
+    # "resize_mode": 0,
+    # "show_extras_results": False,
+    # "gfpgan_visibility": 0,
+    # "codeformer_visibility": 0,
+    # "codeformer_weight": 0,
+    # "upscaling_resize": 1,
+    # "upscaling_resize_w": 4096,
+    # "upscaling_resize_h": 4096,
+    # "upscaling_crop": False,
+    # "upscaler_1": "SwinIR_4x",
+    # "upscaler_2": "R-ESRGAN 4x+ Anime6B",
+    # "extras_upscaler_2_visibility": 0.5,
+    # "upscale_first": False,
+    # "imageList": [
+    # {
+    #     "data": img1,
+    #     "name": "C:\\Users\\y\\code\\ppainter\\restored_image_1.jpg"
+    # }
+    # ]
+    # }
+
+    headers = {"Content-Type": "application/json"}
+
+    response = requests.post(url, data=json.dumps(data), headers=headers)
+
+    if response.status_code == 200:
+        print("Request was successful")
+        response_data = response.json()
+        output_image_path = "Sres_inpainted_{}.png"
+        base64_to_image(response_data["image"], output_image_path.format(str(i)))
+        print(f"Saved output image to {output_image_path.format(str(i))}")
+    else:
+        print(f"Request failed with status code {response.status_code}")

Tex_Remap.py

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+import base64
+import io
+import json
+import requests
+from PIL import Image
+import yaml
+def image_to_base64(image_path):
+    with Image.open(image_path) as img:
+        buffer = io.BytesIO()
+        img.save(buffer, format="PNG")
+        return base64.b64encode(buffer.getvalue()).decode()
+
+def base64_to_image(base64_data, output_path):
+    img_data = base64.b64decode(base64_data)
+    img = Image.open(io.BytesIO(img_data))
+    img.save(output_path, format="PNG")
+
+with open("Render_config.yaml", "r") as f:
+    config = yaml.safe_load(f)
+sd_model = config["sd_model_checkpoint"]
+img1 = image_to_base64("tex_fusion.png")
+bin_uv = image_to_base64("binary_uv.png")
+bin_uv_layout = image_to_base64("binary_uv_layout.png")
+
+img_list = [img1]
+url = "http://127.0.0.1:7860/sdapi/v1/img2img"
+# model_list = requests.get("http://127.0.0.1:7860/sdapi/v1/sd-models")
+# print(model_list.text)
+for i,img in enumerate(img_list):
+    data = {
+        "init_images": [img],
+
+        'prompt': 'vrass,textured',
+        'negative_prompt': 'blur,motion blur',
+        'enable_hr': False,
+        'denoising_strength': 0.2,
+        # 'hr_upscaler': 'Latent (bicubic)',
+        # 'hr_scale': 1.0,
+        'seed': -1,
+        'sampler_name': 'Euler a',
+        'batch_size': 1,
+        'steps': 20,
+        #'quick_steps': 20,
+        'cfg_scale': 7,
+        'width': 512,
+        'height': 512,
+        # 'override_settings': {'CLIP_stop_at_last_layers': 1},
+        'override_settings': {'sd_model_checkpoint': 'imageToVroidStudio_12.ckpt'},
+
+        # 'override_settings_restore_afterwards': 'false',
+        # 'hr_second_pass_steps': 20, 
+    "alwayson_scripts": {
+        "controlnet": {
+        "args": [
+            {
+            "enabled":True,
+            # "module":"tile_resample",
+            "input_image": bin_uv_layout,
+            "model": "control_v11p_sd15_seg",
+            "resize_mode": 0,
+            "processor_res":512,
+            "weight":1,
+            # "threshold_a":1
+
+            },
+            {
+            "enabled":False,
+            "input_image": bin_uv,
+            # "module":'invert',
+            "model": "control_v11p_sd15s2_lineart_anime",
+                "resize_mode": 0,
+                "processor_res":512,
+            "weight":0.5
+
+            },
+            {
+            "enabled":True,
+            "module":"tile_resample",
+            "input_image": img,
+            "model": "control_v11f1e_sd15_tile",
+            "resize_mode": 0,
+            "processor_res":2048,
+            "weight":1,
+            "threshold_a":1
+            }
+        ]
+        }
+    }
+    }
+
+    headers = {"Content-Type": "application/json"}
+
+    response = requests.post(url, data=json.dumps(data), headers=headers)
+
+    if response.status_code == 200:
+        print("Request was successful")
+        response_data = response.json()
+        output_image_path = "tex_remap_{}.png"
+        base64_to_image(response_data["images"][0], output_image_path.format(str(i)))
+        print(f"Saved output image to {output_image_path.format(str(i))}")
+    else:
+        print(f"Request failed with status code {response.status_code}")

Tex_sres.py

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+import base64
+import io
+import json
+import requests
+from PIL import Image
+
+def image_to_base64(image_path):
+    with Image.open(image_path) as img:
+        buffer = io.BytesIO()
+        img.save(buffer, format="PNG")
+        return base64.b64encode(buffer.getvalue()).decode()
+
+def base64_to_image(base64_data, output_path):
+    img_data = base64.b64decode(base64_data)
+    img = Image.open(io.BytesIO(img_data))
+    img.save(output_path, format="PNG")
+
+
+img1 = image_to_base64("tex_tile_0.png")
+
+img_list = [img1]
+url = "http://127.0.0.1:7860/sdapi/v1/extra-single-image"
+for i,img in enumerate(img_list):
+    data = {
+    "resize_mode": 1,
+    "show_extras_results": False,
+    "gfpgan_visibility": 0,
+    "codeformer_visibility": 0,
+    "codeformer_weight": 0,
+    # "upscaling_resize": 0,#By how much to upscale the image, only used when resize_mode=0.
+    "upscaling_resize_w": 4096,
+    "upscaling_resize_h": 4096,
+        "upscaling_crop": False,
+        "upscaler_1": "4x-UltraSharp",
+        # "upscaler_2": "4x-UltraSharp",
+        # "extras_upscaler_2_visibility": 0.5,
+        "upscale_first": False,
+    "image": img
+    }
+    # data = {
+    # "resize_mode": 0,
+    # "show_extras_results": False,
+    # "gfpgan_visibility": 0,
+    # "codeformer_visibility": 0,
+    # "codeformer_weight": 0,
+    # "upscaling_resize": 1,
+    # "upscaling_resize_w": 4096,
+    # "upscaling_resize_h": 4096,
+    # "upscaling_crop": False,
+    # "upscaler_1": "SwinIR_4x",
+    # "upscaler_2": "R-ESRGAN 4x+ Anime6B",
+    # "extras_upscaler_2_visibility": 0.5,
+    # "upscale_first": False,
+    # "imageList": [
+    # {
+    #     "data": img1,
+    #     "name": "C:\\Users\\y\\code\\ppainter\\restored_image_1.jpg"
+    # }
+    # ]
+    # }
+
+    headers = {"Content-Type": "application/json"}
+
+    response = requests.post(url, data=json.dumps(data), headers=headers)
+
+    if response.status_code == 200:
+        print("Request was successful")
+        response_data = response.json()
+        output_image_path = "Tex_sres_{}.png"
+        base64_to_image(response_data["image"], output_image_path.format(str(i)))
+        print(f"Saved output image to {output_image_path.format(str(i))}")
+    else:
+        print(f"Request failed with status code {response.status_code}")