Create app.py

app.py

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+import gradio as gr
+from transformers import QwenProcessor, QwenForVisionAndLanguageGeneration
+import torch
+
+# Load the Qwen-VL model and processor (on CPU)
+processor = QwenProcessor.from_pretrained("Qwen/Qwen-VL")
+model = QwenForVisionAndLanguageGeneration.from_pretrained("Qwen/Qwen-VL")
+
+# Define the function to process the video and return analysis
+def analyze_exercise(video_path):
+    # Create the message prompt for exercise analysis
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "video",
+                },
+                {
+                    "type": "text",
+                    "text": (
+                        "Analyze the exercise shown in the video. "
+                        "Please provide details about the exercise type, the number of repetitions, "
+                        "and an estimate of calories burned during the video."
+                    )
+                }
+            ]
+        }
+    ]
+
+    # Generate the prompt and inputs
+    text_prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
+
+    # Prepare inputs for the model with the uploaded video
+    inputs = processor(
+        text=[text_prompt],
+        videos=[video_path],
+        padding=True,
+        return_tensors="pt"
+    )
+
+    # Generate model output
+    output_ids = model.generate(**inputs, max_new_tokens=1024)
+
+    # Decode and return the text output
+    output_text = processor.batch_decode(
+        output_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True
+    )
+    
+    return output_text[0]
+
+# Set up the Gradio interface
+with gr.Blocks() as app:
+    gr.Markdown("## Exercise Video Analyzer")
+    gr.Markdown("Upload a video to analyze the exercise, count repetitions, and estimate calories burned.")
+    
+    video_input = gr.Video(label="Upload Exercise Video")
+    text_output = gr.Textbox(label="Exercise Analysis")
+
+    analyze_button = gr.Button("Analyze Exercise")
+
+    # When analyze button is clicked, call the analyze_exercise function
+    analyze_button.click(analyze_exercise, inputs=video_input, outputs=text_output)
+
+# Launch the app
+app.launch()