[Community Pipeline] Unclip Image Interpolation (#2400)

* unclip img interpolation poc

* Added code sample and refactoring.

Author: Abhinay1997

Diff for: examples/community/README.md

@@ -28,6 +28,7 @@ Stable Diffusion v1.1-1.4 Comparison | Run all 4 model checkpoints for Stable Di
 MagicMix | Diffusion Pipeline for semantic mixing of an image and a text prompt | [MagicMix](#magic-mix) | - | [Partho Das](https://github.com/daspartho) |
 | Stable UnCLIP | Diffusion Pipeline for combining prior model (generate clip image embedding from text, UnCLIPPipeline `"kakaobrain/karlo-v1-alpha"`) and decoder pipeline (decode clip image embedding to image, StableDiffusionImageVariationPipeline `"lambdalabs/sd-image-variations-diffusers"` ). | [Stable UnCLIP](#stable-unclip) | -  |[Ray Wang](https://wrong.wang) |
 | UnCLIP Text Interpolation Pipeline | Diffusion Pipeline that allows passing two prompts and produces images while interpolating between the text-embeddings of the two prompts | [UnCLIP Text Interpolation Pipeline](#unclip-text-interpolation-pipeline)                   | -                                                                                                                                                                                                                  | [Naga Sai Abhinay Devarinti](https://github.com/Abhinay1997/) | 
+| UnCLIP Image Interpolation Pipeline | Diffusion Pipeline that allows passing two images/image_embeddings and produces images while interpolating between their image-embeddings | [UnCLIP Image Interpolation Pipeline](#unclip-image-interpolation-pipeline)                   | -                                                                                                                                                                                                                  | [Naga Sai Abhinay Devarinti](https://github.com/Abhinay1997/) | 
 
 
 
@@ -989,3 +990,47 @@ The resulting images in order:-
 ![result_3](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPTextInterpolationSamples/resolve/main/lion_to_cub_3.png)
 ![result_4](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPTextInterpolationSamples/resolve/main/lion_to_cub_4.png)
 ![result_5](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPTextInterpolationSamples/resolve/main/lion_to_cub_5.png)
+
+### UnCLIP Image Interpolation Pipeline
+
+This Diffusion Pipeline takes two images or an image_embeddings tensor of size 2 and interpolates between their embeddings using spherical interpolation ( slerp ). The input images/image_embeddings are converted to image embeddings by the pipeline's image_encoder and the interpolation is done on the resulting image_embeddings over the number of steps specified. Defaults to 5 steps. 
+
+```python
+import torch
+from diffusers import DiffusionPipeline
+from PIL import Image
+
+device = torch.device("cpu" if not torch.cuda.is_available() else "cuda")
+dtype = torch.float16 if torch.cuda.is_available() else torch.bfloat16
+
+pipe = DiffusionPipeline.from_pretrained(
+    "kakaobrain/karlo-v1-alpha-image-variations",
+    torch_dtype=dtype,
+    custom_pipeline="unclip_image_interpolation"
+)
+pipe.to(device)
+
+images = [Image.open('./starry_night.jpg'), Image.open('./flowers.jpg')]
+#For best results keep the prompts close in length to each other. Of course, feel free to try out with differing lengths.
+generator = torch.Generator(device=device).manual_seed(42)
+
+output = pipe(image = images ,steps = 6, generator = generator)
+
+for i,image in enumerate(output.images):
+    image.save('starry_to_flowers_%s.jpg' % i)
+```
+The original images:-
+
+![starry](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPImageInterpolationSamples/resolve/main/starry_night.jpg)
+![flowers](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPImageInterpolationSamples/resolve/main/flowers.jpg)
+
+The resulting images in order:-
+
+![result0](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPImageInterpolationSamples/resolve/main/starry_to_flowers_0.png)
+![result1](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPImageInterpolationSamples/resolve/main/starry_to_flowers_1.png)
+![result2](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPImageInterpolationSamples/resolve/main/starry_to_flowers_2.png)
+![result3](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPImageInterpolationSamples/resolve/main/starry_to_flowers_3.png)
+![result4](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPImageInterpolationSamples/resolve/main/starry_to_flowers_4.png)
+![result5](https://huggingface.co/datasets/NagaSaiAbhinay/UnCLIPImageInterpolationSamples/resolve/main/starry_to_flowers_5.png)
+
+