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import gradio as gr |
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import cv2 |
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from PIL import Image |
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import google.generativeai as genai |
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from dotenv import load_dotenv |
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import os |
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load_dotenv() |
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api_key = os.getenv('api_key') |
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genai.configure(api_key=api_key) |
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def extract_frames(video_path, fps=30): |
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frames = [] |
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cap = cv2.VideoCapture(video_path) |
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if not cap.isOpened(): |
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raise ValueError("Error: Unable to open video file.") |
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original_fps = cap.get(cv2.CAP_PROP_FPS) |
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if original_fps == 0: |
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raise ValueError("Error: Unable to retrieve FPS from video file.") |
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frame_interval = int(original_fps // fps) |
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frame_count = 0 |
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success, frame = cap.read() |
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while success: |
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if frame_count % frame_interval == 0: |
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) |
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pil_image = Image.fromarray(frame) |
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frames.append(pil_image) |
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frame_count += 1 |
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success, frame = cap.read() |
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cap.release() |
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if len(frames) == 0: |
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raise ValueError("Error: No frames extracted from the video.") |
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return frames |
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def generate_prompt(button_list): |
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button_descriptions = ", ".join(button_list) |
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return ( |
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f"Generate structured test cases for the following UI button(s): {button_descriptions}.\n\n" |
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"Functionality\n" |
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"- What the button is supposed to do.\n\n" |
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"Preconditions\n" |
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"- Any requirements before interaction.\n\n" |
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" Test Steps\n" |
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"- Concise steps for executing the test.\n\n" |
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"Expected Results\n" |
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"- What the expected outcome should be.\n\n" |
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"Automated Testing Tools\n" |
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"- Recommended tools for testing.\n\n" |
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"Format the output clearly for easy readability, using bullet points for key details." |
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) |
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def process_video(video_file, buttons_to_test): |
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try: |
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video_path = "uploaded_video.mp4" |
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with open(video_path, "wb") as f: |
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f.write(video_file) |
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frames = extract_frames(video_path, fps=30) |
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button_list = [button.strip() for button in buttons_to_test.split(",")] |
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prompt = generate_prompt(button_list) |
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model = genai.GenerativeModel(model_name="gemini-1.5-pro-latest") |
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response = model.generate_content([prompt]) |
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output_text = response.text if hasattr(response, 'text') else "Error: Invalid response from the model." |
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output_text = output_text.replace("Functionality", "📋 Functionality") |
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output_text = output_text.replace("Preconditions", "🔍 Preconditions") |
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output_text = output_text.replace("Test Steps", "📝 Test Steps") |
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output_text = output_text.replace("Expected Results", "✅ Expected Results") |
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output_text = output_text.replace("Automated Testing Tools", "🛠️ Automated Testing Tools") |
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return output_text |
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except Exception as e: |
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return str(e) |
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iface = gr.Interface( |
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fn=process_video, |
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inputs=[ |
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gr.File(label="Upload Video", type="binary"), |
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gr.Textbox(label="Buttons/Functions to Test (comma-separated)", placeholder="e.g., booking, cancel"), |
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], |
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outputs="text", |
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title="UI Test Case Generator", |
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description="Upload a video and specify the buttons you want to test. The tool will generate structured test cases." |
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) |
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iface.launch(share=True) |
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