Update README.md

README.md

@@ -51,7 +51,7 @@ base_model: black-forest-labs/FLUX.1-dev
 instance_prompt: null
 license: mit
 ---
-# twoview-incontext-beta
+# MultiView-InContext-Lora
 
 <Gallery />
 
@@ -59,6 +59,46 @@ license: mit
 
 Inspired by [In-Context-LoRA](https:&#x2F;&#x2F;github.com&#x2F;ali-vilab&#x2F;In-Context-LoRA), this project aims to generate multi-view images of the same scene or object simultaneously. By using flux with the multiview-incontext-lora, we can divide the images into portions to obtain novel views.
 
+> **_NOTE:_** This is a beta release of the model. The consistency between views may not be perfect, and the model might sometimes generate views that don't perfectly align or maintain exact object positions across viewpoints. I am working on improving the geometric consistency and spatial relationships between generated views.
+
+
+## Roadmap
+
+- [ ] 🔄 Improve the consistency between the two-view images.
+- [ ] 4️⃣ Generate 4 views of a scene in a grid format.
+- [ ] 🧸 Generate 4 canonical coordinates view points of a single object in a grid format.
+- [ ] 🏛️ 3D reconstruction from multi-view images.
+
+## Inference
+
+```python
+import torch
+from diffusers import FluxPipeline
+
+pipeline = FluxPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-dev",
+    torch_dtype=torch.bfloat16,
+)
+pipeline.load_lora_weights(
+    "ysmao/multiview-incontext",
+    weight_name="twoview-incontext-b01.safetensors",
+)
+pipeline.fuse_lora()
+
+scene_prompt = "a living room with a sofa set with cushions, side tables with table lamps, a flat screen television on a table, houseplants, wall hangings, electric lights, and a carpet on the floor"
+prompt = f"[TWO-VIEWS] This set of two images presents a scene from two different viewpoints. [IMAGE1] The first image shows {scene_prompt}. [IMAGE2] The second image shows the same room but in another viewpoint."
+image_height = 576
+image_width = 864
+output = pipeline(
+    prompt=prompt,
+    height=int(image_height),
+    width=int(image_width * 2),
+    num_inference_steps=30,
+    guidance_scale=3.5,
+).images[0]
+
+output.save("twoview-incontext-beta.png")
+```
 
 ## Download model