Added controlnet-pose support

Author: gblong1

README.md

@@ -9,7 +9,7 @@ This branch is currently under development. <br>Dedicated for GIMP 3, Python 3 a
 [2] Style-Transfer <br>
 [3] Inpainting <br>
 [4] Semantic-Segmentation <br>
-[5] Stable-Diffusion (Suppports - SD 1.4, SD 1.5 (landscape & portrait), SD 1.5 Inpainting) <br>
+[5] Stable-Diffusion (Suppports - SD 1.4, SD 1.5 (landscape & portrait), SD 1.5 Inpainting, SD 1.5 Controlnet-Openpose) <br>
 
 # Objectives
 [1] Provides a set of OpenVino based plugins that add AI features to GIMP. <br>
@@ -86,10 +86,22 @@ Skip steps 1 and 2 if you already have Python3 and Git on Windows
 #### C. Stable-Diffusion-1.5 Inpainting - Make sure to download and convert the model during install process. 
 1. Choose a layer or Open an image of size 512x512. (Currently works best with this resolution) <br>
 2. Use "Free select tool" to select the area in your image that you wish to change. <br>
-3. Right click on you image and click on "Add layer mask". Then choose "Selection" in "Initalize layer Mask to". This should create a mask with your selection.
+3. Right click on your image and click on "Add layer mask". Then choose "Selection" in "Initalize layer Mask to". This should create a mask with your selection.
 4. Follow steps 2,3,4,5 from section A. Please note that you will only see "SD_1.5_Inpainting" in model options if you added a mask layer to your image. <br>
 5. Click on “Run Inference”. Wait for the total inference steps to get completed. <br>
 
+
+#### D. Stable-Diffusion-1.5 Controlnet-Openpose - Make sure to download and convert the model during install process. 
+1. Open an image with some pose that you want to see in new image. <br>
+2. Select Stable Diffusion from the drop down list in layers -> OpenVINO-AI-Plugins <br>
+3. Choose the controlnet_openpose model and device from the drop down list.<br>
+4. Make sure to select -- "Use Initial Image" option from the GUI. If not selected then it will fail. 
+5. Follow steps 4,5 from section A. <br>
+5. Click on “Run Inference”. Wait for the total inference steps to get completed. <br>
+
+![](gifs/controlnet-openpose.png)
+
+
 *If create gif option is selected, please note that performance will reduce. The generated gif is located in below path. You can play it in GIMP by going to Filters -> Animations -> Playback* <br>
 ```C:\Users\<user_name>\openvino-ai-plugins-gimp\gif\stable_diffusion.gif``` <br>
 

choose_sd_model.py

@@ -6,9 +6,13 @@
 if platform.system() == "Linux":
     sd_python_path=os.path.join(".", "model_conv/bin/python3")
     chose_model=os.path.join(os.path.dirname(__file__), "sd_model_conversion.py")
+    chose_model_controlnet=os.path.join(os.path.dirname(__file__), "controlnet_model_conversion.py")
 else:
     sd_python_path=r'model_conv\Scripts\python.exe'
     chose_model=r'openvino-ai-plugins-gimp\sd_model_conversion.py'
+    chose_model_controlnet=r'openvino-ai-plugins-gimp\controlnet_model_conversion.py'
+    
+
 
 print("=========Chose SD-1.5 models to download and convert=========")
 print("1 - Square (512x512 output image) ")
@@ -17,32 +21,37 @@
 print("4 - Portrait_512x768 (512x768 output image), will take time since model is large ")
 print("5 - Landscape_768x512 (768x512 output image),  will take time since model is large ")
 print("6 - SD-1.5 Inapinting model (512x512 output image) ")
-print("7 - ALL the above SD-1.5 models ")
-print("8 - Only Square, Landscape, Portrait")
-print("9 - Skip All SD-1.5 Model setup ")   
+print("7 - SD-1.5 Controlnet-Openpose model (512x512 output image) ")
+print("8 - ALL the above SD-1.5 models ")
+print("9 - Only Square, Landscape, Portrait")
+print("10 - Skip All SD-1.5 Model setup ")   
 
 while True:
     choice = input("Enter the Number for the model you want to download & convert: ")
 
     # setup all the SD1.5 models
-    if choice=="7":
+    if choice=="8":
         for i in range(1,7):
 
             subprocess.call([sd_python_path, chose_model, str(i)])
-            
+        
+        subprocess.call([sd_python_path, chose_model_controlnet, "7"])    
         break
     # setup only square, landscape and Portrait
-    elif choice=="8":
+    elif choice=="9":
         for i in range(1,4):
 
             subprocess.call([sd_python_path, chose_model, str(i)])
         break
-    elif choice=="9":
+    elif choice=="10":
         print("Exiting SD-1.5 Model setup.........")
         break
     elif choice in ["1","2","3","4","5","6"]:
 
         subprocess.call([sd_python_path, chose_model, choice])
+    elif choice == "7":
+  
+        subprocess.call([sd_python_path, chose_model_controlnet, choice]) 
 
         break