Removed video model

.idea/.name

@@ -0,0 +1 @@
+app.py

app.py

@@ -70,14 +70,14 @@ def load_image_model():
      pipeline.load_lora_weights("LoRA dataset/Weights/pytorch_lora_weights.safetensors", weight_name="pytorch_lora_weights.safetensors")
      return pipeline
 
-@st.cache_resource
-def load_video_model():
-    pipeline = I2VGenXLPipeline.from_pretrained("ali-vilab/i2vgen-xl", torch_dtype=torch.float16, variant="fp16")
-    return pipeline
+# @st.cache_resource
+# def load_video_model():
+#     pipeline = I2VGenXLPipeline.from_pretrained("ali-vilab/i2vgen-xl", torch_dtype=torch.float16, variant="fp16")
+#     return pipeline
 
 A2C_model = load_text_model()
 image_service = load_image_model()
-video_model = load_video_model()
+#video_model = load_video_model()
 
 if "audio_input" not in st.session_state:
     st.session_state.audio_input = None
@@ -104,18 +104,15 @@ if st.session_state.audio_input:
         if st.button("Generate Image and video from text prompt"):
             st.session_state.image = image_service(st.session_state.captions).images[0]
             image = st.session_state.image
-            video = video_model(
-                prompt = st.session_state.captions,
-                image=st.session_state.image,
-                num_inference_steps=50
-            ).frames[0]
-            st.session_state.video = video
-            export_to_video(video, "generated.mp4", fps=7)
-            c1,c2 = st.columns([1,1])
-            with c1:
-                st.image(image)
-            with c2:
-                st.video("generated.mp4")
+            # video = video_model(
+            #     prompt = st.session_state.captions,
+            #     image=st.session_state.image,
+            #     num_inference_steps=50
+            # ).frames[0]
+            # st.session_state.video = video
+            # export_to_video(video, "generated.mp4", fps=7)
+            st.image(image)
+