Add a visual gallery demonstration

README.md

@@ -4,7 +4,7 @@ The entire project is divided into two parts: `text_or_gloss2pose` and `pose2vid
 
 - In the text2pose section (`Expected 4 seconds / one video`), I first used the DWpose tool to extract the npz format pose information for each word video frame by frame, and then merged each frame's npz into a large npz file. That is to say, we know the consecutive poses corresponding to each word. These consecutive poses are stored in the merged npz file. (We can also use deep learning models to generate these poses, but for commercial-level accuracy, this original data Dict method will be much more accurate.) 
 
-- In the pose2video section (`Expected 4 minutes / one video`), we render the visualized poses of the skeletons generated by each word. I used the ControlNext-SVD model for this. 
+- In the pose2video section (`Expected 6 minutes / one video`), we render the visualized poses of the skeletons generated by each word. I used the ControlNext-SVD model for this. 
 
 # For Users
 
@@ -41,6 +41,48 @@ CUDA_VISIBLE_DEVICES=0 python ControlNeXt-SVD-v2/run_controlnext_optimized.py \
   --decode_chunk_size 2
 ```
 
+## Demo Gallery
+
+<details>
+<summary>🎬 Click to view generated examples</summary>
+
+### Example 1: "good morning afternoon"
+- **Input text**: `good morning afternoon`
+- **Pose video**: `generated_pose_video/GOOD_MORNING_AFTERNOON_25073_36863_01435_20250803_233215.mp4`
+- **Final video**: `generated_sign_video/GOOD_MORNING_AFTERNOON_25073_36863_01435_20250803_233215.mp4`
+- **Combined view**: `generated_sign_video/GOOD_MORNING_AFTERNOON_25073_36863_01435_20250803_233215_combined.mp4`
+
+### Example 2: "hello world"
+- **Input text**: `hello world`
+- **Pose video**: `generated_pose_video/HELLO_WORLD_27184_63831_20250803_235543.mp4`
+- **Final video**: `generated_sign_video/HELLO_WORLD_27184_63831_20250803_235543.mp4`
+- **Combined view**: `generated_sign_video/HELLO_WORLD_27184_63831_20250803_235543_combined.mp4`
+
+### Example 3: "I will attend this dinner party"
+- **Input text**: `I will attend this dinner party`
+- **Pose video**: `generated_pose_video/I_WILL_ATTEND_THIS_DINNER_PARTY_28794_63364_04007_66628_16327_41325_20250803_235750.mp4`
+- **Final video**: `generated_sign_video/I_WILL_ATTEND_THIS_DINNER_PARTY_28794_63364_04007_66628_16327_41325_20250803_235750.mp4`
+- **Combined view**: `generated_sign_video/I_WILL_ATTEND_THIS_DINNER_PARTY_28794_63364_04007_66628_16327_41325_20250803_235750_combined.mp4`
+
+### Example 4: "not find yet"
+- **Input text**: `not find yet`
+- **Pose video**: `generated_pose_video/NOT_FIND_YET_38868_21853_38946_20250803_235630.mp4`
+- **Final video**: `generated_sign_video/NOT_FIND_YET_38868_21853_38946_20250803_235630.mp4`
+- **Combined view**: `generated_sign_video/NOT_FIND_YET_38868_21853_38946_20250803_235630_combined.mp4`
+
+### Example 5: "where is my cat"
+- **Input text**: `where is my cat`
+- **Pose video**: `generated_pose_video/WHERE_IS_MY_CAT_63084_58616_37469_65313_20250803_235927.mp4`
+- **Final video**: `generated_sign_video/WHERE_IS_MY_CAT_63084_58616_37469_65313_20250803_235927.mp4`
+- **Combined view**: `generated_sign_video/WHERE_IS_MY_CAT_63084_58616_37469_65313_20250803_235927_combined.mp4`
+
+### Note on video types:
+- **Pose video**: Shows the skeleton/pose generated from input text/gloss
+- **Final video**: The rendered sign language video with a virtual signer
+- **Combined view**: Side-by-side comparison of pose and final video
+
+</details>
+
 
 # For developers
 

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