Update README.md

README.md

@@ -22,22 +22,26 @@ base_model:
 
 ## 🛠️ Usage
 
+Install MEMFOF via the package manager:
+
 ```shell
-git clone https://github.com/msu-video-group/memfof.git
-cd memfof
-pip3 install -r requirements.txt
+pip3 install git+https://github.com/msu-video-group/memfof
 ```
 
+Then use the following snippet to compute backward and forward optical flow for three consecutive frames:
+
 ```python
 import torch
-from core.memfof import MEMFOF
+from memfof import MEMFOF
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model = MEMFOF.from_pretrained("egorchistov/optical-flow-MEMFOF-Tartan-T-TSKH-spring").eval().to(device)
 
 with torch.inference_mode():
-    example_input = torch.randint(0, 256, [1, 3, 3, 1080, 1920], device=device)  # [B=1, T=3, C=3, H=1080, W=1920]
-    backward_flow, forward_flow = model(example_input)["flow"][-1].unbind(dim=1)  # [B=1, C=2, H=1080, W=1920]
+    # [B=1, T=3, C=3, H=1080, W=1920]
+    example_input = torch.randint(0, 256, [1, 3, 3, 1080, 1920], device=device)
+    # [B=1, C=2, H=1080, W=1920]
+    backward_flow, forward_flow = model(example_input)["flow"][-1].unbind(dim=1)
 ```
 
 ## 📚 Citation